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  By George V. what does that imply? By Christopher S. By Ping Gao and Jiang Yu 33 Kode Vicious Print is Not Just Ink Anymore By David Roman 37 Calendar 19 125 Careers Presenting Your Project The what. and the why of giving an effective presentation. By Kirk L. By Jack Rosenberger Is the Internet a Maturing Market? If so. Kroeker Gödel Prize and Other CS Awards Sanjeev Arora. the how. health. in one of his last interviews before his death in 2002. 10 CACM Online 17 Has China Caught Up in IT? An assessment of the relative achievements in IT infrastructure. Kroeker Making Sense of Real-Time Behavior Data captured by sensors worn on the human body and analyzed in near real-time could transform our understanding of human behavior. and other researchers are recognized for their contributions to computer science. Michael Bernstein discusses Clay Shirky’s keynote speech at CSCW 2010. By Samir Chopra 41 Interview An Interview with Edsger W. By Kirk L.B. and More Greg Linden asks if spammers have been defeated. Neville-Neil 35 Privacy and Security Remembrances of Things Pest Recalling malware milestones. and Erika S. By Thomas J. Spafford 38 Viewpoint Last Byte 128 Puzzled Figures on a Plane By Peter Winkler 21 Rights for Autonomous Artificial Agents? The growing role of artificial agents necessitates modifying legal frameworks to better address human interests. Poole writes about how the digital world can help parents cope with the death of a child. Joseph S. 5 3 | NO. By Gary Anthes Looking Beyond Stereoscopic 3D’s Revival Researchers working in vision and graphics are attempting to develop new techniques and technologies to overcome the current limitations in stereoscopic 3D. firms. 8 . By Eugene H. Misa Association for Computing Machinery Advancing Computing as a Science & Profession 2 communicaT io nS o f T he ac m | AU g U ST 201 0 | VO l . and communication protocols. reflects on a programmer’s life. Dijkstra The computer science luminary. By Sarah Underwood Celebrating the Legacy of PLATO The PLATO@50 Conference marked the semicentennial of the computer system that was the forerunner of today’s social media and interactive education. By David S.communications of the acm Departments 5 News 11 Viewpoints 24 Economic and Business Dimensions JACM Editor’s Letter JACM at the Start of a New Decade By Victor Vianu 6 7 In the Virtual Extension Letters To The Editor Mechanism Design Meets Computer Science A field emerging from economics is teaming up with computer science to improve auctions. Touretzky 30 Emerging Markets The War Against Spam. and innovation in China. Mitchell. and society. supply chains. Yoo 27 Education CS Expertise for Institutional Review Boards 8 BLOG@CACM 14 Preparing Computer Science Students for the Robotics Revolution Robotics will inspire dramatic changes in the CS curriculum.
  acm. 8 | c om m u n ic aT ion S of T he acm 3 . 80 Review Articles 90 about the cover: the singularity system. to ensure timely publication. modern programming languages let Microsoft rethink the architectural trade-offs in its experimental operating system. By Mache Creeger Seven Principles for Selecting Software Packages Everything you always wanted to know but were afraid to ask about the decision-making process. Ve articles undergo the same rigorous review process as those in the print edition and are accepted for publication on their merit. Elie Bursztein. 08 Practice 48 Contributed Articles Research Highlights 104 Technical Perspective Software Development with Code Maps Could ubiquitous hand-drawn code map diagrams become a thing of the past? By Robert DeLine. Microsoft research’s effort to build a microkernelbased operating system. Rothenberger IllustratIon by st udIo to nne AU g U ST 2 0 1 0 | VO l. england. Huberman 115 Reasoning About the Unknown in Static Analysis By Isil Dillig. the system draws parallels to the singularity model where physical laws as we know them are no longer valid.08/2010 vol. For more on the studio’s work. Haines and Marcus A. Boehm Intelligent Service Machine Wei-Feng Tung and Soe-Tsyer Yuan Thinkflickrthink: A Case Study on Strategic Tagging Eugenio Tisselli Plat_Forms: Is There One Best Web Development Technology? Lutz Prechelt How a Service-Oriented Architecture May Change the Software Development Process Marc N. page limitations often prevent the publication of articles that might otherwise be included in the print edition. and Dan Boneh 114 Technical Perspective Large-Scale Sound and Precise Program Analysis By Fritz Henglein 72 63 The Singularity System Safe. aCM created Communications’ Virtual extension (Ve).studiotonne. By Jan Damsgaard and Jan Karlsbjerg Articles’ development led by queue. By James Larus and Galen Hunt Predicting the Popularity of Online Content Early patterns of Digg diggs and YouTube views reflect long-term user interest.org Attacks Target Web Server Logic And Prey on XCS Weaknesses By Helen Wang 105 The Emergence of Cross 55 Channel Scripting By Hristo Bojinov. is the focus of this month’s cover story as told by the projects’ lead researchers James larus and Galen Hunt. 53 no. these articles are now available to aCM members in the digital library. see. rendering this concept for the cover is Paul Farrington from studio tonne. Memory Models: A Case for Rethinking Parallel Languages and Hardware Solving the memory model problem will require an ambitious and crossdisciplinary research direction. By Sarita V. By Gabor Szabo and Bernardo A. Adve and Hans-J.com. Gina Venolia. an illustrative agency based in brighton. and Alex Aiken Virtual Extension as with all magazines. Thomas Dillig. 53 | N O. and Kael Rowan Moving to the Edge: A CTO Roundtable on Network Virtualization Leading experts debate how virtualization and clouds impact network service architectures.
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  this would quickly consume the current annual page budget of 1. Principles of Programming Languages (POPL). We currently have or are exploring such arrangements with annual symposiums. JACM plays a special role among ACM publications. With the field expanding and becoming increasingly diversified. First published in January 1954. consists of inviting a small number of papers selected from top conferences in targeted subfields. and computeraided verification.ucsd. Much of JACM’s focus has been on theory of the flavor found at the Symposium on Theory of Computing (STOC) and Foundations of Computer Science (FOCS). Even areas with very strong theoretical sides have minimal representation. This approach is appealing because it no longer leaves coverage of underrepresented areas entirely up to the chance of spontaneous submissions. since it is considered risky to have much fewer papers in the publication pipeline. This is reasonable. machine learning. even slides or videos of talks.200 pages. notes. 53 | N O. For both reasons. the DL provides substantial added value in the form of cross-links and searchable metadata.acm. allowing researchers to keep up with the state of the art across the entire discipline.jacm editor’s letter DOI:10. 8 | c om m u n ic aT ion S of T he acm 5 . JACM’s new information director. Let us say. In contrast. highly selective venue. it seems the right time to share some thoughts on how ACM’s oldest publication is doing and where it might be headed. will play a central role in shaping JACM’s online presence. only one bioinformatics paper and one computer architecture paper were published in this period. its charter of publishing the best research across computer science—as broadly construed—is a tall order. for quite some time. this remains a controversial idea. I am working with the board to keep the processing time under a year for most papers eventually accepted. A new Web site for JACM has also been launched (. At an average of 40 pages per paper. Besides advantages of cost and scalability. FOCS. JACM fulfills a complementary role by publishing in a single. Web systems and algorithms. and none were accepted in software engineering. JACM papers are currently published in e-form in ACM’s Digital Library. hypothetically. Pierre Senellart. One of the often-cited drawbacks of journals versus conferences is the long wait from submission to publication. I believe such content is appealing to both readers and authors. A proactive approach to ensuring top-quality representation from a wider spectrum of areas. including cryptography. There are several possible explanations for the difficulty in attracting top-quality papers in some areas. according to at least one bibliometric authority (. Of the 93 articles published in JACM over the past three years.edu) is a professor of computer science and engineering at university of California. The move coincided with the start of a new decade. There also seems to be a (mis) perception that some topics are not welcome to JACM. publications in some of the emerging or cross-boundary areas have been slow to follow. it is the top-ranked journal in computer science. Overall. Victor Vianu (vianu@cs.00 AU g U ST 2 0 1 0 | VO l. Communications of the ACM provides magazine-style content appealing to all ACM members—academics and practitioners—and includes select research articles showcasing the “best of the best” results originally presented in ACM proceedings. appendices. Transactions publish high-quality research in a specific subfield of computer science. aiming for comprehensive coverage of the area. In the case of JACM. Principles of Database Systems (PODS). Principles of Distributed Computing (PODC). logic in computer science. Conference publications are increasingly favored over journal publications in many subfields. I believe JACM is going strong. Yet JACM is facing nontrivial challenges. initiated by Prabhakar Raghavan. coupled with the physical limitations and cost of JACM as a print journal.org/). This makes the notion of forgoing the print edition in favor of an online-only publication increasingly tempting. and conferences such as Research in Computational Molecular Biology (RECOMB) and Computer Aided Verification (CAV). or six months. that we aim to publish annually the three best papers in 10 subfields of computer science. Another advantage is the ability to post additional content on home pages of articles. I am confident the journal will pursue its upward trajectory in the coming years. However.eigenfactor. the publication queue has hovered around three issues. As such. One way to counteract this is to ensure visible representation of such areas on the editorial board. Indeed. However. An orthogonal obstacle to comprehensive coverage is simply due to the proliferation of areas to be covered. software engineering. In summary.org/map). san diego. It is a widely respected publication.1145/1787234. Past editors-in-chief have worked to expand the scope of JACM beyond this core. several editors have now been appointed representing such areas as bioinformatics. JACM is the flagship scientific publication of the ACM. such as errata. the best research in all areas of computer science.1787235 Victor Vianu JACM at the Start of a new Decade It has been almost a year since I assumed the editor-in-chief role for Journal of the ACM (JACM). Logic in Computer Science (LICS). and computational economics. and shorter for papers that are eventually rejected. © 2010 aCM 0001-0782/10/0800 $10. JACM is facing some growing pains but it is thriving. approximately 35 are still in core algorithms and complexity. and we will aim to provide it on a regular basis. including STOC.
  5 3 | NO. using different technology platforms.1145/1787234.1787269 Marc N.o rg /s ub s Medical Informatics: Why So Slow? Research in Computing: The Myth of Rapid Obsolescence Performance Evaluation and Model Checking Join Forces Point/Counterpoint on the Future of Internet Architecture Injecting Errors for Fun and Profit Thinking Clearly About Performance ht tp :// w w w.1145/1787234. Adding to this impetus are the efforts related to open standards and open source products. This article reports on the setup of the contest and some results of this study. such as completeness (reflecting productivity). including online protest. intelligent Service machine DOI:10. Rothenberger The service-oriented approach to IT architecture has become an important alternative to traditional software development. 6 comm unicaTio nS o f T he ac m | AU gU ST 201 0 | VO l . enabling a systematic and quantitative delivery of service operation using self services. showcasing emerging innovations and industry leaders from around the world across important applications of design thinking and the broadening field of the interaction design. applying technology to education.1787237 in the Virtual extension Communications’ Virtual Extension brings more quality articles to ACM members.1787270 Eugenio Tisselli A tag can be created and disseminated for strategic purposes. These articles are now available in the ACM Digital Library. and size. The resulting systems were thoroughly evaluated with respect to many criteria.1145/1787234.1145/1787234. Readers should expect to see some prevalent prejudices confirmed and others firmly refuted. The authors present a machine-aware service-system design framework (iDesign) and an ISM-supported service system to demonstrate the notion and the framework. and technology. 8 . In this article. Thinkflickrthink: a case Study on Strategic Tagging DOI:10. maintainability. and how it can augment the users’ potential for direct action. a And the latest news on computational neurobiology. how a Service-oriented architecture may change the Software Development Process DOI:10. the notion of service machine is defined as a socio-technical system with the shared reality of customer and provider aiming for the joint optimization of productivity and satisfaction. Haines and Marcus A. Coming Next Month in COMMUNICATIONS cr ib e cm . and MIT’s Big Wheel and smart bikes. ACM’s interactions magazine explores critical relationships between experiences. Plat_forms: is There one Best Web Development Technology? DOI:10. Three teams used Java EE.in the virtual extension DOI:10.1787271 Lutz Prechelt Plat_Forms is a contest in which three-person teams of professional programmers competed to implement the same requirements for a Web-based system within two days. But one key question remains: Are service-oriented architecture (SOA) adopters ready for this change and will they be able to provide a technical and organizational environment in which SOA-related technologies can be leveraged to their full potential? This article explores the development process and methodology that may require adjustments in order to provide a good fit for SOA development. An intelligent service machine (ISM) moves beyond service machine by modeling and automating the cognitive process and knowledge representations of the machine’s embodied theory. and three used PHP. Our readers represent a growing community of practice that is of increasing and vital global importance. three used Perl. The study of the dynamics of uncoordinated semantic strategies within dense online communities is of enormous importance to gain a greater understanding of how social and linguistic interaction takes place in a networked environment. The research presented in this article analyzes one particular protest strategy adopted by a number of users of Flickr: the use of anti-censorship tags to make the protest visible within the site itself. people.1787268 Wei-Feng Tung and Soe-Tsyer Yuan Machine is a metaphor that can be used to expand the capability of service systems and ‘think’ for innovative service system design.1145/1787234. robustness (hinting at security).
  Finally. included in the article’s references and is apparently not available. Garfinkel. Never expect a usability test to find all problems. the authors assumed the length of the IRB review process represents a problem with the process itself though offered only anecdotal evidence to support this assumption. Four to eight participants should be included if the aim is to drive a useful iterative cycle: Find serious problems. For example. Sadly. however. May 2010) was timely. J. the number and quality of usability test moderators affects results more than the number of test participants. the size of a participant group depends on the purpose of the test. and dumas. it did not address several important issues concerning numbers of study participants: Most important. Deception research. with varying backgrounds to promote complete and adequate review of research activities commonly conducted by the institution. the authors created a dichotomy of computer scientists and IRBs. So go for a small number of participants. Possibilities include inefficient IRBs and uninformed and/or unresponsive researchers. the number is huge. Moreover. © 2010 aCM 0001-0782/10/0800 $10.S. r. which was not. from a recent discussion with the authors. Second. they likely know where to look. observe behavior in discussion forums and virtual worlds. I now understand that the published research in the article was carried out in 2004 or earlier and the article was submitted for publication in 2006 and accepted in 2008. Comparative usability evaluation (Cue-4). Though Wonil Hwang’s and Gavriel Salvendy’s article “Number of People Required for Usability Evaluation: The 10±2 Rule” (Virtual Extension. how many Participants needed to Test usability? No usability conference is complete without at least one heated debate on participant-group size for usability testing. Communications welcomes your opinion. that “many computer scientists are unfamiliar with the IRB process” and “may be reluctant to engage with their IRB. requiring more deliberation. they will be forced to do so. as one of the computer scientists newly elected as an American Academy 2010 Fellow. and lack visibility among CS researchers in their organizations. computer scientists would likely find it easier to approach their IRB. the column was timely but also somewhat misleading. Indiana University.” However. PA find some of them.acm. 263–281. michael R. some proposals may just be more ethically complex.00 AU g U ST 2 0 1 0 | VO l. It is also quite clear that if we do not come up with a solution. This limitation has important implications on the size of a test group. First. it should have listed Jon Michael Dunn. federal regulations (45 CFR 46. Molich. and perform Facebook-related research. to submit a letter to the editor. long used in social sciences. Monterey. Pittsburgh. lack sufficient representation of members with CS knowledge. as with any deception research.1787236 cS expertise for institutional Review Boards I RBs n e e d com pu teR scientists. Two such anecdotes involved research on phishing. In this regard. an intrinsically deceptive phenomenon. likely in the thousands. our experience is that most IRBs in the U. say. It would also mitigate another problem explored in the column. Not just over the nature of certain CSrelated research but because social scientists (and others) administer online surveys. aiming to. using them to drive a useful iterative cycle where the low-hanging fruit is picked/fixed in each cycle.S. Stenløse. please limit your comments to 500 words or less and send to letters@cacm. dissertation.107(a)): “Each IRB shall have at least five members.” Indeed. 8 | c om m u n ic aT ion S of T he acm 7 . Also. correct them. 53 | N O. CUE-studies1 show it is impossible or infeasible to find all problems in a Web site or product. The authors directed my questions to the first author’s Ph.1145/1787234. Scheessele. saying IRB “chairs from many institutions have told us informally that they are looking to computer scientists to come up with a workable solution to the difficulty of applying the Common Rule to computer science. find more serious problems. All references in the article are from 2004 or earlier.org. Simson L.” Before developing a technical solution to perceived IRB delays. CA Lorrie faith cranor. IN authors’ Response: Scheessele is correct in saying an increasing number of social scientists use computers in their research and is yet another reason IRBs should strive to include a computer scientist as a member.D. Behaviour & Information Technology 27. Rolf molich. a point highlighted by the Viewpoint “Institutional Review Boards and Your Research” by Simson L. In addition. any institution conducting a significant amount of humansubjects research involving computing and IT ought to include a computer scientist on its IRB. The IRB shall be sufficiently qualified through the experience and expertise of its members…” Though CS IRB members do not have all the answers in evaluating human-subject research involving computing and IT. We apologize for these errors. two or three participants should be included if the main goal is political. Denmark Reference 1. are understaffed. typically takes longer to review because it runs counter to the ethical principle of “respect for persons” and its regulatory counterpart “voluntary informed consent.letters to the editor DOI:10. the typical causes of delay must be established. 3 (May 2008). Garfinkel and Lorrie Faith Cranor (June 2010). per U. if an IRB member is just down the hall. demonstrate to skeptical stakeholders that their product has serious usability problems and usability testing can correction “CS and Technology Leaders Honored” (June 2010) mistakenly identified the American Academy of Arts and Sciences as the American Association for the Advancement of Science. South bend.
  Michael Bernstein discusses Clay Shirky’s keynote speech at CSCW 2010. Annoyances flooded most inboxes. with only 28 sales out of 350 million messages sent. In that respect. features more than a dozen bloggers in the BLoG@cacm community. and more Greg Linden asks if spammers have been defeated. we’ll publish selected posts or excerpts. Huge email campaigns that attempt to work around spam filters require sophistication to devise and run. Today. Despite prostituting my email addresses undisguised across the Internet.1787238 http:/ /cacm.1145/1787234. and many other tricks to evade detection. the war would be lost. I can flag it as non-spam to teach the filter and add the sender to a white list. email spam appears to be a solved problem. Email address lists have to be purchased and maintained.00001%. I know e-postage proposals haven’t gotten very far in the past. If you’re receiving hundreds of spam emails a day.acm. in each issue of Communications. sending email from a new company like mine that hasn’t established itself with the many filters out there [is] very time consuming and inefficient. Poole writes about how the digital world can help parents cope with the death of a child. adding additional text to emails. and that is welcome.acm.005%. as an entrepreneur. 8 . However. and Erika S.org/blogs/blog-cacm point that even massive and complicated spam efforts like the Storm botnet generate surprisingly low revenues for what appears to be the work required. the filters would be overwhelmed. despite receiving hundreds of spam messages daily. but their increasingly complicated efforts have not been able to outwit the filters.00001% then the postage can be a lot lower as well. What is your own experience with email spam? Do you think the spam war been won? Or are these declarations of victory premature? Reader’s comment: I would argue that your declaration of victory is premature. the drop in response rates from 2003 to 2008 may be close to making spam an unprofitable enterprise.org. It appears to be getting to the | AU g U ST 201 0 | VO l . First and foremost. Spam filters appear to have forced down response rates three orders of magnitude in five years. email spam was a dire problem. Amazingly. as you wrote. I imagine more than a few false positives slip by you. 5 3 | NO. follow us on Twitter at. I think that would clean up a lot of email inboxes. and my spam folder as well.org/ blogs/blog-cacm/78121 A decade ago. from companies and small businesses sending to a small list rather than the mass splattering of true email spam. If there was a proactive way for a legitimate sender to register itself and either post a bond or pay e-postage. and email readers would be buried under an avalanche of spam.The Communications Web site. but not for the obvious reason that spam in the inbox has been reduced. The ones that I do see typically are borderline spam. Greg Linden’s “has the Spam War Been Won?”. but if the spam response rate is now down to 0. There is a substantial amount of effort required to attack and manage a botnet of 1 million compromised machines that can cheaply send 12 million messages per day.com/blogcacm DOI:10. two problems remain. 8 communicaTio nS o f T he acm trying to customize each email sent. has gone way down in recent years. but that is reactive. there is still the problem of false positives. A 2003 study put response rates at 0. Once I do find a desired email. nearly zero make it to my inbox. I still have to check my spam folder because the filters will occasionally falsely flag a legitimate email. Any attempt to read your email started with deleting the crud that had leaked through your defenses.. spam in my inbox. The second reason we can’t declare victory just yet is the very fact that the The War against Spam. My own experience is that email spam has become a non-issue. Spammers have fought back with misspellings.acm. Many predicted the problem would only get worse. A 2008 study where the authors infiltrated a major spam botnet found response rates had fallen to under 0. A few predicted that email would be dead in just a few years. Additionally.
  your boss tells you to do something. pay me $10 for a lab study and I’ll use anything for an hour!) Usability is a local hillclimbing algorithm. Unfortunately. etc. Erika Shehan Poole is an assistant professor at the school of Information sciences and technology at Penn state university. and disorienting experience? For some parents. but we’re not there yet. In a keynote delivered to this year’s ACM Conference on Computer Supported Cooperative Work (CSCW). 53 | N O. For example. work (little w) is motivated by inherent interest and is generally unpaid. Think of the difference between an Encyclopedia Britannica editor doing Work and a Wikipedia editor doing work during spare hours. but it is a horrible determiner of utility on a grander scale. Reader’s comment: Jared Spool.edu/~mikem/hcieol/. By contrast. —Ed H. He really wanted to solve the usability problem. and could not. Big Work drives the economy. talked about compelled shopping tasks in which people were actually given money to buy things on Internet sites. whether it’s derived from the design process or social science. we have to continue to apply technological fixes to our networks and teach people not to be so gullible. Yet a user base didn’t flock to MSN—the portal simply could not attract and retain as many users as it wanted. but also realized that decoupling the motivational issues with usability is difficult. what would they look like? I had the opportunity to speak with Mike Massimi. and have been studied by scholars in other disciplines for centuries. Individual computers continue to get infected and people still foolishly click on requests from Nigerian princes. candidate at University of Toronto who’s examining these questions for his thesis work. then they will simply send spam in other forms such as on Twitter. Extrapolating on my own here: Usability is an important refinement technique when you have a good idea. Greg Linden is the founder of Geeky Ventures. Mike is working extensively with two community organizations in the Ontario area that provide social support to parents who have suffered the loss of a child. We shouldn’t be asking. Poole’s “Death and the Digital World”. (Sure. Work (Capital W) is what we have considered for years. Yet technology researchers and designers are just now starting to come to grips with how to design with end-of-life experiences in mind. dgp. In particular. Clay argued that user-testing techniques developed over the past 25 years for Work no longer apply for work.D. an event in which new scholars discuss their work with a panel of experts. —Will Hartmann “usability is an important refinement technique when you have a good idea. technology for work instead needs to understand users’ underlying motivations. 8 | c om m u n ic aT ion S of T he acm 9 .d. a Ph.org/ blogs/blog-cacm/72837 um. painful. I wish we could declare victory. “Can you complete the task?” but rather “Are you mo- tivated to do it in the first place?” Excel needs usability testing because people are forced to use it for Work.blog@cacm spammers and their resources. Big Work builds skyscrapers. little work drives the Internet.00 At the Computer Supported Cooperative Work 2010 conference. both botnets and humans. If email spam continues to become less and less profitable. Death and dying are experiences as old as humanity. I couldn’t help but notice that the students invited to this year’s event presented work highlighting the deeply human side of information technology. little work generates a half-million fan fiction stories about Harry Potter. and respectful technologies that help bereaved parents mourn and remember their lost children. Develop that and you could save thousands of man-hours developing tools that nobody will ever want to use. Yet how are bereaved parents using technologies to grieve and mourn? If we were to design technologies that help people cope with grieving and loss in meaningful and respectful ways. Big ‘W’ Work suggests that we are going to have to dig much deeper into this issue than we had before. Chi bernsteIn PH otoGra PH by Jason d orF M an erika S. We need techniques to make and evaluate that miraculous motivational leap. His next step is to create meaningful. student in the Computer science and artificial Intelligence lab at Massachusetts Institute of technology. Mike co-hosted the first workshop (ever!) focused on death and the digital world at the ACM CHI 2010 conference. remain alive and well. students received invitations to participate in the Doctoral Colloqui- AU g U ST 2 0 1 0 | VO l. In addition to being a great opportunity for students. How do you cope with such a traumatic. © 2010 aCM 0001-0782/10/0800 $10.toronto. Little ‘w’ work vs.acm. To understand how technology plays a role in modern grieving.org/ blogs/blog-cacm/72609 MSN usability researchers were stumped. and you get paid. information technologies can play an important role in the grieving and mourning process. Believe me. author and academic Clay Shirky captured this question in a distinction between Work and work. Their usability lab had tested just about every aspect of its MSN portal and had been pleased to find that it consistently scored higher than its competitors. appropriate. You can see more info about the workshop at. or Doing Work?”. imagine you’re a parent who has suffered the unthinkable: Your child has died. Michael Bernstein is a Ph. the Doctoral Colloquium highlights some of the most exciting work in the field from promising young scholars. you do it. but it is a horrible determiner of utility on a grander scale. Then Clay Shirky relayed the million-dollar question: Were these tasks that users actually wanted to do? Or were these highly usable aspects of the site going to remain unused because nobody wanted to use them? There was a gaping hole between usability and usefulness.” michael Bernstein’s “clay Shirky: Doing work.D. Facebook. If you’re interested in learning more about this topic. 13 Ph. for years.
  and the ones we do produce don’t understand parallel programming. The goal of each format is to give users the content they want. but on full-screen and mobile systems. some of the most exciting of these involve better human-computer interfaces and interactions with the physical world.ly uRL. chief scientist and senior vice president of research of nVIdIA corp. DaLLy WinS eckeRT-mauchLy aWaRD Acm and Ieee computer society jointly presented the eckert-mauchly Award to William J. and Inez Kerr Bell professor of computer science and electrical engineering at stanford university. developed the system and network architecture. and synchronization technology that is found in most of today’s large parallel computers. We aren’t producing enough cs graduates. dally singled out “cs education. “At present I’m working on low-power computer architecture. “I really enjoy seeing how parallel computing enables new applications that weren’t possible before. have cleared the way for mobile apps Communications is going mobile. Like other publications. it will continue to evolve. for his innovative contributions to the architecture of interconnection networks and parallel computers. every course needs to be redesigned around parallelism. flipable pages. where. introduced in January 2008. and may become a component of a digital-first publishing strategy. routing.org/dl). A great example is augmented reality— where parallel computing enables realtime computer vision to interpret the image you see. Digital Editions. that will tailor content to handhelds. was introduced in 1996. and adds other articles. The VE’s status is evidenced by the readership of its most popular articles listed here. dally. Communications has expanded over time into a variety of electronic formats for e-connected members and readers. It’s particularly rewarding that this work is likely to have a measurable positive impact on the environment. daily news. the print edition publishes only their summaries.org) moves magazine content into HTML. when. Like Communications’ other formats.ly/9JHOlh. who is also the Willard R.” —Jack Rosenberger 10 communicaT io nS o f T h e acm | AU gU ST 201 0 | VO l .org/ communications) present complete issues with familiar. Originally conceived as an outlet for articles that did not fit into page-constraints of the print edition. The VE is establishing itself as a destination for authors and readers. Each format delivers something its counterparts do not. query a database. saying.acm. dally discussed his current research in an email interview. teaching parallelism isn’t just an add-on to the existing curriculum. first as a biannual collection of articles available only in e-format—a pioneering step in publishing circles back then.ly/bodbNO. the VE is coming into its own. 8 PHotoGra PH by a ndrIJ bo rys .ly/cyNF8g.. and annotate the image with useful information.1787239 David Roman Print is not Just ink anymore The world of Communications is not contained in the pages of a monthly magazine.ly/b0oaKt. plus access to ACM’s abundant member services. particularly education about parallelism. and it’s very exciting that there are opportunities where innovation can make a large difference in efficiency.cacm online ACM Member News DOI:10. now in development. Digital Editions (. having evolved as a monthly editorial fixture since September 2008. and how they want it.1145/1787234. blogs. Articles from Communications’ Virtual Extension (VE) are available from the Web site and ACM’s Digital Library (. and a mobile Web site.ly/cJlye7. Communications’ brand began taking e-steps before the relaunch of the Communications Web site in April 2009.ly/amhrsp WiLLiam J. in fact. 5 3 | NO. dally. article Principles for effective Virtual Teamwork Capstone Programming Courses Considered Harmful Number of People required for Usability evaluation: 10±2 rule An Overview of IT Service Management Why Did Your Project Fail? The requisite Variety of Skills for IT Professionals A Holistic Framework for Knowledge Discovery and Management Bit.acm. The Web site (. The concept of the VE. signaling. It’s interesting to find out where the power actually goes in a modern computer. which is on par with and in some cases exceeds that of print issue cover stories.” Asked about important cs issues.ly/dCSgY0.
  n T h e Bo u n d ARIe s se pARAtIn g news Science | DOI:10. and communication protocols. and economics becomes more complex. As work in computers. Information technologists are turning these concepts into such disparate applications as auction management. supply chains. from network design to distributed computing to operating systems. or society at large. which emerged from economic game theory in the 1970s. mechanism design expresses ideas that are elegantly simple. is now shaking hands with information technology. mechanism design is enabling advances in information tech- in the DaRPa network challenge. a DARPA director. and how to do that in an adversarial environment. Last December. “We wanted to understand how you could rapidly mobilize a very large team to solve a hard problem. they have private information.S. Built on a formal mathematical base.1145/1787234. teams used mechanism design and social networking techniques to locate the defense agency’s 10 geographically dispersed. and the matching of organ donors and recipients. the physical and social sciences. Also. DARPA’s challenge: Be the first team to find all 10 balloons. nology. so does the motivation for practitioners to seek help from each other. and may act in ways that can’t be observed.1787240 Gary Anthes mechanism Design meets computer Science A field emerging from economics is teaming up with computer science to improve auctions. biology. Meanwhile. DARPA wanted to learn how teams 11 PHotoGra PH Court esy oF da rPa AU g U ST 2 0 1 0 | VO l. Success would depend on a competitor’s ability to assemble a large group of geographically dispersed volunteers. The DARPA Network Challenge from the Defense Advanced Research Projects Agency (DARPA) offers one example. 53 | N O. DARPA tethered 10 red weather balloons at undisclosed locations across the continental U. computer science and other disciplines are blurring at an accelerating pace. and they may lie. red weather balloons. 8 | c om m u n ic aT ion S of T he acm .” says Peter Lee. The central goal in mechanism design is to devise a system by which those people will tend to act in ways that benefit the owner of the system. yet tricky to apply in the real world: people in competition will act “rationally” to meet their own selfish goals. supply chain optimization. with a social networking twist. Mechanism design.
  who recruits D. with lots of constraints. The DARPA experiment was not conceived specifically as an exercise in mechanism design.000. D finds a balloon and gets $2. a computer scientist at Hebrew University in Jerusalem.” Meanwhile. such as communication bandwidth. repeatedly over time. he has pioneered automated mechanism design.” Mechanism design can provide a framework for optimizing those protocols. director of the Agent-Mediated Electronic Marketplaces Laboratory at Carnegie Mellon University. including the winning one from Massachusetts Institute of Technology (MIT). and estimates that two million people received email. mechanism design is also being used to solve problems of network congestion. Likewise. and the auction would simply find it. for example. won an NSF grant to develop auction software that allows bidders to specify budget constraints. making auctions Pay Tuomas Sandholm. For example. Buyers. 5 3 | NO.000 people signed up to assist the MIT team. who recruits C.” says Noam Nisan. via old media.” Sandholm says. An obvious financial incentive would be to promise anyone who found and reported a balloon to the winning team a part of the $40. it’s the challenge of efficiently allocating a given resource. could. TCP/IP communication protocols are based on the assumption that when a computer sees congestion. learn more about the resource’s value by using it.000 for posting a tweet. a research engineer at Georgia Tech.” Milgrom’s early work. For example. “Everyone was incentivized to get the word out.000. C gets $1. stretching back some three decades. Auctionomics. it ends up being squeezed away completely. Nisan says that all work on communication protocols today should consider the fact that computers are connected yet controlled by “different. profitably employed those principles. clearly is not at an end. Last year. But more recently he’s worked with combinatorial auctions. co-designed the simultaneous ascending auction used by the U. finding nine balloons in a largely more traditional way.S. The first person to report a balloon gets $2. has taken the basic concepts of mechanism design and extended and implemented them in novel ways. “But when TCP competes for bandwidth with other ‘non-polite’ protocols. where there often is no such single price and the computation of efficient outcomes is generally NP-hard. and that’s mechanism design. For example. Milgrom’s work with mechanism design. “Some of the best work in this area has been done by computer scientists. or Facebook requests for help. designed by Sandholm. The second-place team from Georgia Institute of Technology did almost as well. including an article in The Wall Street Journal and an interview on National Public Radio. “It’s a very complex optimization problem for both parties. “The auction broke all records for sale of public property and has been widely copied in other countries.000. For example.” says Ethan Trewhitt.” says Galen Pickard. Paul Milgrom. the MIT team found all 10 balloons in less than nine hours by devising a clever way to motivate a large number of volunteers through a recursive incentive scheme. Some teams did just that. More generally.” Pickard says 5. “Yet no existing mechanism enables effective competition when bidders face serious budget constraints. That put Georgia Tech near the top of the results in a Google search for “DARPA Red Balloon.” NSF notes. 8 . Managing the resulting complexity demands the application of computer science techniques. According to the National Academy of Sciences. Twitter. and more payments propagate through the chain back from that person. it will temporarily delay sending data. The MIT team recruited an initial cadre of volunteers via email. or users. Many real-world applications of mechanism design are complex indeed. B gets $500. an economist at Stanford University. Milgrom says he’s working on dynamic resource allocation auctions in which. The miT team located all 10 red balloons in less than nine hours by devising a clever way to motivate a large number of volunteers through a recursive incentive scheme. in which participants can bid for individual items or packages of items.000 prize money. “There were people who actually made $1. “The crowdsourcing thing was not as big a thing as the old media. in the 1980s.” he says. a computer and cognitive scientist at MIT. he says. selfish entities. a company he started. 12 com municaTio nS o f T h e ac m | AU g U ST 201 0 | VO l . mostly dealt with situations in which there was a market-clearing or equilibrium price. Lee says. Federal Communications Commission in its sale of radio spectrum licenses in the mid-1990s. he cites recent research—namely. “Multi-item auction design has been at the frontier of research in economics and computer science over the past 15 years.” while the National Science Foundation (NSF) hailed it as a “victory for the field of game theory. a seller might have to decide to accept a bid now or wait for a better one tomorrow. P&G uses a mechanism design-based combinatorial auction.” Milgrom says. then encouraged each volunteer to establish a personal chain of participants: A recruits B. which is used for Internet routing among competing domains.news would use social networks and crowdsourcing as this might aid in military intelligence gathering. in combinations specified by them. “Interdomain Routing and Games” by economist Hagay Levin and computer scientists Michael Schapira and Aviv Zohar from the Hebrew University of Jerusalem—that shows that the Border Gateway Protocol (BGP). But the MIT team knew it not only had to motivate people to look for and report balloons. such as UDP. and so on. by which complex mechanisms are devised by computers. but many of the teams. not humans. but also to find lots of additional people to help them locate the balloons. and A gets $250. which are machines built for this purpose. Procter & Gamble (P&G) seeks to optimize its supply chain by getting annual bids for trucking services across North America.
  and if these Isps would shut down or block these compromised computers.” Potential Pitfalls To be sure. “the Role of Internet service providers in Botnet migration: An empirical Analysis Based on spam data. Designing the perfect auction.. Algorithmic mechanism design. often. “Working with lawyers is a lot harder than making Web sites.” he says.” the researchers note. there are pitfalls in the application of mechanism design ideas. clusters of reported balloon sightings that contained identical coordinates. one gets an entire “graph” of bids and preferences. and that knowledge can lead to behaviors that are both undesirable and not predicted by theory. T. August 2008. For example. says MIT’s Pickard.org/nobel_prizes/ economics/laureates/2007/ecoadv07. Va.. Papadimitriou. Nisan. as much of economic theory assumes.00 Procter & Gamble uses a mechanism design-based combinatorial auction in which participants can bid for individual items or packages of items. but “actual human behavior is a lot more complicated and superficially ‘irrational’ than the predictions made by theoretical models.000 Isps. But if an auction is repeated. C. Communications of the ACM 51. notions of rationality may be mathematically pure in economics. it would drastically curtail the delivery of spam. Computing in mechanism design.” the researchers presented their paper. A related issue is that the mechanism and the problem it is trying to solve may together be so complicated as to be computationally intractable. such as an auction where instead of a single point bid from each bidder. August 15. and are now working with the dutch government to create metrics of Isps’ efforts to detect and shut down compromised computers. S. R. in isolation.K. with some teams even automating their detection. Gary Anthes is a technology writer and editor based in arlington. 8 | c om m u n ic aT ion S of T he acm . The New Palgrave Dictionary of Economics (2nd ed. Finally.. because the choice of how much to invest in bid preparation is not a choice that is included in most theoretical models of behavior. in combinations specified by them. It’s not sufficient to tell them. to the third decimal. Sami. be made “incentive-compatible.. this is a remarkable finding.com/videoplay?doc id=6121409064231775355#. Of the 200 red balloon sightings reported to the MIT team. were Cybersecurity How Top ISPs Could Reduce Spam the zombie computers responsible for sending more than half of the world’s spam reside on the networks of the leading 50 Isps. 1. “We spent four days winning the DARPA Network Challenge and about two months working out how to pay people. DARPA’s Lee says teams detected false reports in some clever ways.” Nisan says. the most elegant of ideas can have unintended consequences. H. For example. “don’t worry.” Further Reading Feigenbaum. 2007. © 2010 aCM 0001-0782/10/0800 $10.news with certain security enhancements. Distributed Computing 18. 80% were false. 2008.. Shenker. That approach introduces “an interesting twist. a professor of public administration at delft university of technology in the netherlands. “the top 50 Isps account for over half of all [spam] sources worldwide. Palgrave Macmillan. such as regarded as fake because real sightings from multiple people always have some slight variation.” Lee says. a computer science professor at Cornell University. Similarly. N. —Jack Rosenberger 13 AU g U ST 2 0 1 0 | VO l. 53 | N O. 15. buyers and bidders learn something about each other. Basingstoke. “Many of the results that we got for free from economic theory stop working when there are approximations.” Kleinberg says. these unsolicited messages are mailed by computers that have been hijacked by criminals and turned into a large network of remotely controlled machines known as a botnet. Royal Swedish Academy of Sciences. U.” at the Workshop on the economics of Information security at harvard university.” Kleinberg says. Nisan is a pioneer in the field of algorithmic mechanism design. The computational ability of participants and their incentives are intertwined in complex ways. says mechanisms may be so complicated that users don’t understand them and hence won’t participate.google. Oct. according to a team of researchers led by michael van eeten.” That is..000 [Autonomous system numbers] and anywhere between 4.000 and 100. 8. A BGP-based mechanism for lowest-cost routing. Varian. 2007. Google Tech Talks video. eeten and his colleagues analyzed more than 63 billion unsolicited email messages sent from 2005–2008 and discovered that some 138 million unique Ip addresses were linked to the messages’ delivery. Robert Kleinberg. “In light of the fact that there are 30. And the cost of information gathering in order to bid can distort results. And there’s that nasty bit about lying. J. Sandholm says another potential pitfall is evaluating one event. “So there is this general concept of being able to use relatively straightforward data-mining techniques to quickly derive the characteristics between good and bad information.). users would no longer have any reason to deviate from BGP. by which systems find good approximations of optimal solutions in computationally hard problems. one of P&G’s combinatorial auctions. July 2005.pdf Sandholm. I have proved a theorem that the best thing for you to do is such-and-such. Prize Committee Mechanism design theory.
  “I enjoyed viewing Avatar. and I experienced no discomfort during the three-hour showing. for example. Converging the eyes drives focus to a nearer distance. one kind of cue is motion parallax. several fundamental depth-cue issues have yet to be resolved. requiring special cameras. 8 . are the same. which means that vergence distance and focus distance are coupled in the brain. the market for stereoscopic 3D computers is expected to grow rapidly. many of which have remained unchanged since the 19th century. called the focus distance. ESPN and other broadcasters are rolling out dedicated 3D cable channels. distinct challenges remain. with one million units shipped this year and 75 million by 2014. This disparity causes a 14 | AU gU ST 201 0 | VO l . glasses. with the most recent example being the Samsung SCH-W960. according to Jon Peddie Research (although most of these computers will be stereoscopic 3D-capable due to their graphics processors. visualization. Also. which conveys depth through apparent object movement. called the vergence distance. the distance at which each eye’s line of sight must converge. and the distance at which the eyes must focus. they’ll still require a special monitor.news Technology | DOI:10. a principal researcher at Microsoft Research Silicon Valley. New research has found.1145/1787234. stereoscopic 3D is being used more subtly as an aspect of storytelling to enhance immersion into environments that appear to invite the viewer inside. or were annoyed by certain cinematic techniques. and content). “But many people I’ve spoken with did experience discomfort. while movies can render parallax for camera motion correctly. and new 3D products expected this year from major manufacturers such as LG. a smartphone designed to convert 2D content automatically into stereoscopic 3D. attempting to develop new techniques to overcome the limitations associated with traditional stereoscopic 3D strategies. projectors. Television manufacturers and broadcasters have fallen under the spell of the third dimension. The film Avatar is a testament to this shift in how moviemakers now use stereoscopic 3D. which is a big improvement over previous cinematic experiences. After all. Panasonic. display technology. Researchers working in this area—a field that draws on vision science. they remain far from mature. the content remains costly to produce and cumbersome to consume. One of these issues is how the human brain perceives simulated 3D differently from how it perceives the natural world. who cofounded Silicon Graphics and led the development of OpenGL. Kurt Akeley. and cognitive science—are communicaT io nS o f T h e acm kurt akeley is experimenting with an approach related to light-field theory in which the display is replaced with a volumetric light source so light comes directly from the simulated distance. For example. with stereoscopic 3D TVs and Blu-ray players now widely available. specific physiological reasons for the visual fatigue that viewing stereoscopic 3D media sometimes causes. In the physical world. And mobile device-makers have begun to incorporate 3D technology into their handhelds. When looking out the side window of a moving vehicle. While it might not be difficult to imagine movie theaters one day tracking head movement to render viewerbased motion parallax correctly. while focusing to a nearer distance drives the eyes to converge. objects beside the road appear to move past the window more quickly than objects in the distance. and glasses. despite head movement and regardless of seat position in the theater.” There are several kinds of depth cues that researchers working in this area are actively studying to improve such stereoscopic 3D experiences. Stereoscopic 3D media requires that viewers fix their eyes at simulated distances but still focus on the display’s fixed distance. S t e R e o s c o p I c 3 d I s experiencing a strong resurgence. everybody in an audience sees the same image on the screen. and yet the movie industry is not alone in embracing the technique. And while the technology for creating such media has become more sophisticated. Kroeker Looking Beyond Stereoscopic 3D’s Revival Researchers working in vision and graphics are attempting to develop new techniques and technologies to overcome the current limitations in stereoscopic 3D. Currently. says that while stereoscopic 3D techniques and technologies are growing more sophisticated. for instance.1787241 Kirk L. In today’s cinema. with moviemakers no longer using the technique primarily as a gimmicky audience-draw consisting of objects poking from the screen into the theater space. and Sony. While the stereoscopic 3D resurgence continues to have a powerful impact on consumer culture. 5 3 | NO. they cannot create parallax to account for a viewer’s head movement. such as the limited depth of field in many scenes.” says Akeley.
  89 D Focal Demand = 0. “I’m hopeful that this virtuous cycle of researchers using industry-created equipment to probe human visual mechanisms and create useful feedback for industry will accelerate as stereoscopic viewing becomes the standard. While the images are presented in counter-phase to the two eyes. To address this issue.” he says. particularly when the viewer’s distance is likely to be short.5 D Mid-Near Lens Power = 5. “We think this is potentially a serious problem with the distribution of stereoscopic media. 8 | c om m u n ic aT ion S of T he acm 15 . each image is shown three times before it is updated.” he says. a pair of custom-designed dynamic lenses constructed with birefringent material. 53 | N O. images are presented to the left and right eye at 72 cycles per second.9 D AU g U ST 2 0 1 0 | VO l. The idea is to replace the display with a volumetric light source so light comes directly from the simulated distance. Berkeley. the idea has proven to be difficult to implement in practical applications outside the lab. as with small TV screens viewed at a short distance. Akeley remains optimistic about such research. Banks has conducted widely cited studies showing how this conflict between fixed display depth and vergence distance causes visual discomfort.3 D Far-Mid Mid-Near Lens Power = 5. Far 1a Far-Mid 1b Mid-Near Far Far Lens Power = 6. understanding Depth cues Another researcher focused on depth cues in stereoscopic 3D is Martin Banks.69 D Focal Demand = 1.news physiological disconnect that can lead to headaches and even nausea. The lenses are used to create a volumetric stereoscopic 3D display with four apparent image depths. The update rate is only 24 cycles per second. Rendering illuminates pixels in inverse proportion to their distance from the simulated distance.09 D Focal Demand = 2. a professor of vision science at the University of California. “We still have lots to learn about how stereoscopic signals affect how people perceive things.29 D Focal Demand = 1. In stereoscopic 3D cinema. simulated distance.7 D Far-Mid Far-Mid Mid-Near Far Lens Power = 6. essentially eliminating the gap between vergence distance and focus distance. The prototype systems are mainly used to help understand human perception and the effects of forcing users to focus at one distance while looking at an object at a different.” Banks is currently working on how the presentation of information over time affects the perception of motion and depth cues. Akeley has been experimenting with an approach related to light-field theory. creating a seamless sense of depth. a coarse approximation of what it would be in the natural figure 1a and 1b. Despite the promise of using lightfield theory to make stereoscopic 3D more comfortable for viewers. which he says has the potential to lead to new strategies for dealing with this disparity. Still.
  “But once we do. the program finds errors in com16 comm unicaTio nS o f Th e ac m puter code for complex parallel programs. P. which makes objects blurry when they are farther from or nearer to the focus distance. 2008. called phases.” Banks says. the primary developers of the program are Lawrence Livermore scientist greg Bronevetsky and purdue doctoral student Ignacio Laguna. B. K.S. high-speed switchable lens enables the development of a volumetric stereoscopic display.J. Hands.” he says. and an overall better understanding of vision fatigue related to focus and depth cues. Girshick. the technique will continue its momentum in moviemaking. A. M. Hoffman. Real world Stereo display vergence distance vergence distance focal distance focal distance display surface only will eliminate the need to wear special glasses. MA.” In a related project. and vision sciences will continue to improve colors so they look more like the natural world. Akeley.M. It also operates by splitting a simulation into numerous windows of time. K. August 2009. Watt. 5 3 | NO. “For these studies. Vergence-accommodation conflicts hinder visual performance and cause visual fatigue.. “We’re a long way from achieving these goals. have created an automated debugging program for the simulations used to certify nuclear weapons. Focus cues affect perceived depth.J. and Banks.W. 8 inefficient to locate the bug. and Banks. A. but also to understand how changes in that relationship affect human perception. but also will have the ability to track head movement to render motion parallax accurately. Watt. collaborating with highperformance computing experts at Lawrence Livermore national Laboratory. The results of such investigations could influence the design of content for stereoscopic 3D cinema and television. Kirk L. –Jack Rosenberger . and Banks.” Microsoft Research’s Akeley. which keeps the analysis simple enough so it can be performed when the simulation is running. it would be useful to have faster display technology than we currently have. Kroeker is a freelance editor and writer specializing in science and technology. M. ACM Transactions on Graphics 23.. © 2010 aCM 0001-0782/10/0800 $10. Journal of Vision 8. A stereo display prototype with multiple focal distances. Banks predicts that.. Banks is conducting studies to determine the relationship between depth-of-field blur and other depth cues.R.J. Banks is studying how blur affects the perception of distance and size. “With such technology. however.” was presented at the 40th Annual Ieee/IFIp International conference on dependable systems and networks in chicago. 10. A..M. Banks is studying how the visual system can tolerate such slow updates and how viewers perceive such signals to be smooth and convincing. Automaded’s approach involves grouping a large number of processes into a smaller number of “equivalence classes” with similar traits. 3D Movie Making: Stereoscopic Digital Cinema from Script to Screen. And he predicts the proliferation of more powerful content-creation technologies.. in the natural world.. which makes it difficult and | AU gU ST 201 0 | VO l .news figure 2. for his part. D. these simulations can last several weeks.S. predicts future 3D displays not Software Automated Debugger for Parallel Programs purdue university researchers. G. Ernst. He also predicts that display update rates will improve to the point where motion looks truly smooth. called Automaded (for automata-based debugging for dissimilar parallel tasks). such as eyes and cameras. International treaties forbid the detonation of nuclear test weapons. M.. and the paper. December 15. and it is common for an error in the simulation code to not become evident until long after it occurs.. based in los angeles. so certification is performed with complex simulations. Girshick.S. D. 18. Hoffman.K. Gao.00 world. K. the experience of watching video will be truly breathtaking. August 2004. S. Kirby. 3. Journal of Vision 5. focus distance (the distance to which the eyes must focus to make an image sharp) and vergence distance (the distance at which the eyes’ lines of sight converge on an object) are the same.. Mendiburu. “Automaded: Automata-Based debugging for dissimilar parallel tasks. we would be able to better understand the consequences of using different temporal protocols in the presentation of stereoscopic video. despite the abundance of unanswered questions about how human perception works with simulated 3D. whether they occur on big screens or small ones.R. such as movie-production systems that can render a scene from different viewpoints without reshooting it. M... M.D. Further Reading Akeley. and Banks. Akeley.O. 2005. Burlington. 3. 3D viewing experiences will be greatly improved. This incongruity can cause headaches and even nausea. can be focused only on one distance at a time. S. With these and other technological advances.. Optics Express 17. March 28. most stereoscopic 3D displays require viewers to point their eyes at simulated distances while still focusing on the display’s actual fixed distance.. J. Focal Press. 2009.. Conventional optical devices. Love.S.
  ” could transform the way we understand ourselves and society (although he adds the caveat that reality mining will raise the bar on data privacy and ownership). a discipline he calls “reality mining. “It’s spying that people don’t like. “As computational social scientists we can build a better model of how people behave than psychologists or sociologists because we can actually see what people are doing.” he says. 53 | N O.” Popular clubs and events Beyond Pentland’s work. which is using smart badges on client projects similar to those undertaken by Pentland.” Having discovered the business benefits of socializing. taxis. Every day.” Pentland suggests that one of reality mining’s uses could be to reduce human errors in hospitals. such as moving employees or knocking down walls to improve communication. more intimate wearable sensors are playing a leading role in understanding human behavior to an extent that has not previously been possible. a professor at Massachusetts Institute of Technology’s Media Lab who specializes in computational social science. but says that most buy in if their boss is included and they can view the data. “Staff who socialize trade information about how to do their jobs better. and a team of researchers with reality-mining devices at massachusetts institute of Technology’s media Lab. With in-depth behavioral knowledge. plastic tags on lanyards. 8 | c om m u n ic aTion S of T he acm .” says Pentland. social interaction has been found to be an important element in productivity. leading a team that used large wearable devices to track human behavior. perhaps identifying stress in the tone of voice as a precursor to mistakes. structuring rest periods and coffee breaks to support social interaction. People who are cut off aren’t wise in the ways of the company and don’t have social support. “If their information is open to them and they have control of it.” he explains. Pentland goes one step further by giving staff and managers control over the data. “Reality mining is about understanding people and situations very rapidly. voice. and location data. Pentland acknowledges that such data-capture schemes could face opposition from staff. “At more than a dozen companies where we have used wearable sensors. Pentland points out that as corporations strive for greater productivity they often structure staff time to reduce personal conversations. right. health. Data from this kind of reality mining can also be analyzed to evaluate office layout and recognize desirable changes. suggests real-time collection and analysis of data about people.news Society | DOI:10. The latter includes Sense Networks. A s t h e p RoLIFe RAtI on of smartphones and networks puts a mobile sensor in many people’s pockets.1787242 Sarah Underwood making Sense of Real-Time Behavior Data captured by sensors worn on the human body and analyzed in near real-time could transform our understanding of human behavior. body language. and through MIT Media Lab spin-offs. 17 PHotoGra PH by rICK F rIed Ma n AU g U ST 2 0 1 0 | VOl. companies typically reorganize. reality mining is reaching the market through companies such as Hitachi Consulting. but their commonality is in collecting fine-grained data that can be computed to visualize real-time behavior. The real-time data would be sent to a central server and analyzed to detect patterns of mistakes. which analyzes mobile location data from cellphones. and sticky plasters. applications can be developed that make the best use of behavioral patterns or monitor behavior to ensure and potentially improve human well being. A similar solution can be used to improve employee productivity. people are generally much happier. and society. such as badges. Alex “Sandy” Pentland. cameras.1145/1787234. Pentland started research on reality mining in the mid-1990s. hospital staff would wear sensor-equipped name badges that capture their tone of alex Pentland. The sensors can be integrated into a variety of wearable items.
  Key considerations and experience using the ultra-low-power Sensium platform in body sensor networks. or the need to recharge their batteries. but continue to be monitored by healthcare professionals. they want to meet.K. Further Reading Burdett. Summer 2009. MA. Lakhanpal. December 11–12. the need to sterilize plasters. 2009. u. “Why invest in more hardware when we could now use what is in people’s pockets?” Borrego asks. even if it was ambulatory. D. A. Mary’s Hospital. Sensium: An ultra-low-power wireless body sensor network platform: design & application challenges.” Continuous ambulatory monitoring could also provide important insights into human health as the vital sign data captured in real time from patients could be correlated to show trends in patient health that cannot be readily understood using traditional methods of data capture that are bulky and have limited portability. “Ultimately.” says chris Toumazou.K. Chris Toumazou. Cambridge. where it is analyzed. A. C. M. The nTag solution uses proprietary hardware. Proceedings of the Annual International Conference of IEEE Engineering in Medicine and Biology Society. Olguin Olguin. The devices are worn on lanyards and support not only real-time attendee tracking. Olguin Olguin. “Our next generation technology will use smartphones and a micro browser. as the analysis of multiple. Wong. P. Mn. Correlation could also provide an extra dimension to alerts.. An MIT Media Lab spin-off is nTag. the success of the event can be measured. Minneapolis. particularly their high-power requirements and that any device built using them would be bulky. Burdett... McPartland. Berkeley. Gloor. 2009. vital sign data could predict adverse patient effects that may occur in hours or even days. R.J. O. Nunn. Pentland. 8 . and delivered to a nurse or doctor. Third International Conference on Pervasive Computing Technologies for healthcare. A. Honest Signals: How They Shape our World. The data is forwarded to a hospital information system. Conference attendees. London..” The digital plaster technology. London.. Toumazou set out to create a low-power technology that could capture data from a body. Three problems. obtrusive. this technology will allow patients to leave the hospital. 2009. For event organizers. Lisbon. “We have commercialized ultra lowpower wireless systems and signal processing. September 3–6. McDonagh. It offers event organizers sensor-laden handheld devices that can be used by event participants. © 2010 aCM 0001-0782/10/0800 $10.. 5 3 | NO.. such as Bluetooth and Zigbee. M. a company founded in 2002 that fell into bankruptcy before being acquired by Alliance Tech in March 2009. Corporate Event Magazine. but also social networking. CA.. Nunn. Pentland. June 3–5. can exchange contact information by pressing a button on their nTag device and later access that information on the event’s Web site. wearable sensors are likely to prevail in the medical field where the automated analysis of real-time data captured by sensors could prove transformational. Mary’s Hospital in London. lege. Silveira. CEO of Toumaz and a professor at the Institute of Biomedical Engineering at Imperial Col18 comm unicaTio nS o f T he ac m Digital plasters will allow “patients to leave the hospital. which has been developed by Toumaz but is expected to be licensed and commercialized. D. such as “Where is everyone this evening?” Another spin-off is Cogito Health. or they can be alerted by an nTag vibration if they are close to someone who.. and paperwork can be reduced by using nTag for activities such as attendee feedback. Sarah Underwood is a technology writer based in teddington.C. “We call this the Sensium technology platform to which sensors can be attached. A. April 2009. Sixth International Workshop on Wearable and Implantable Body Sensor networks. D. further applications of the Sensium technology are anticipated. but continue to be monitored by healthcare professionals.H. “Because of the economies of scale of semiconductors we can drive down cost and make digital plasters disposable. McDonagh. One application that uses Cogito’s vocal signaling platform is a depression-monitoring service that automatically processes care-management telephone calls and allows healthcare professionals to proactively identify patients who may need support for clinical depression.. avoiding problems such as infection. which is developing Pentland’s research to extract meaning from speech behavior.. U. A.news and GPS devices to create a real-time map of popular clubs and events to provide answers to consumers’ questions. Portugal.” says Toumazou. putting them together on a single chip. A. for example.” explains Toumazou. but Alliance Tech CEO Art Borrego says future products will move away from such technology. and possess a short operating life. D.. C. 2008. interpreted. real-time data capture and analysis means changes can be made on the fly during an event..00 | AU gU ST 201 0 | VO l .W. has developed the technology behind a digital plaster concept that is being used in patient trials at St. with Toumazou and his team at the Institute of Biomedical Engineering currently working with the technology to create a diabetes management system that. is expected to be licensed to a commercial partner. MIT Press. like the digital plaster technology. C. This is the basis of the digital plaster. A. Realizing the constraints of existing wireless technologies. according to preselected criteria. Sensible organizations: a sensor-based system for organizational design and engineering. International Workshop on Organizational Design and Engineering. Wearable Sensors for Pervasive healthcare Management. Alliance Tech focuses on marketing intelligence at events such as trade shows and conferences. includes a plaster or patch that sticks to the body and captures vital sign data from patients. Pentland.. Pappas. one solution: attendee surveillance. As trials of the digital plaster continue at St. Omeni. Hernandez-Silveira.” As smartphones become the sensor for many reality-mining applications.
  and Marc Andreessen. “That story is important to tell. and an array of social media content preserved from the original PLATO databases. the Computer His- tory Museum hosted the PLATO@50 Conference to mark the 50-year anniversary of the computer system that many credit with presaging the networked world of social media and interactive education that has become a mainstay of contemporary culture. software. PLATO@50 documented an array of events that occurred at CERL from its inception in 1967 to its closing in 1994. In addition to keynote speeches and moderated discussions. the highlight of which was a moderated discussion between Don Bitzer. “The conference paid tribute to a culture of innovation and openness fostered by Don Bitzer that clearly had an impact on a large number of engineering and computer science majors who passed through CERL and the University of 19 AU g U ST 2 0 1 0 | VO l.1145/1787234. CA-based museum. More than 400 computing enthusiasts attended the event. “PLATO@50 was an important event for the museum to convene. such as Avatar and Empire. including Ray Ozzie. whose initial design for Lotus Notes derived from PLATO Notes.1787261 Kirk L.” says John Hollar. either in original or derivative form. The terminals included many of the original PLATO games. says Hollar. president of the Mountain View. the inventor of PLATO. 53 | N O. CoM Puter H Isto ry M useuM functioning PLaTo terminals were set up for use by PLaTo@50 conference participants. the co-author of Mosaic and founder of Netscape. Kroeker celebrating the Legacy of PLaTo The PLATO@50 Conference marked the semicentennial of the computer system that was the forerunner of today’s social media and interactive education.” The conference. The event included several presentations and a reunion of PLATO alumni from across the U. Microsoft’s chief software architect.news Conference | DOI:10. and applications—that live on today. highlighted how PLATO in the Computer-based Education Research Laboratory (CERL) at the University of Illinois at Urbana-Champaign produced an accomplished group of alumni.S. The terminals included many of the first PLaTo games and an array of social media preserved from the original PLaTo databases. I n eARLy June. functioning PLATO terminals were set up in an interactive “PLATO playground” for use by conference participants. 8 | c om m u n ic aT ion S of T he acm .” says Hollar. As a special part of the conference. PHotoGra PH Court esy oF C arIna sW eet. and Ray Ozzie. “It traced the history of a system that produced the forerunners to an amazing array of technologies—hardware.
  mcclelland professor of management Information systems and director of the Artificial Intelligence Lab at the university of Arizona. institutional historian for the IEEE History Center at Rutgers University. and courseware designer from 1979 to 1984. Kroeker is a freelance editor and writer specializing in science and technology. outperforming the s&p 500 and six of the 10 leading quantitative funds. chat rooms. an acronym for Programmed Logic for Auto- Artificial Intelligence Computer Scientists Beat U. whose book on PLATO. the researchers have expanded their field of research and are now devising systems that can analyze financial writers’ sentiments. “He put together a package of existing and invented technology with educational pedagogy to develop a new way of instruction.” AZFintext’s technique involves surveying financial news and stock prices.” he says. It was used for education and training by many schools and universities. developed by Robert p. and hsinchun chen. “But … you can have an advantage if you look at five minutes. With this quantitative approach. the Arizona Financial text system. AZFintext sells the stocks after 20 minutes.” he says.” says Hochheiser. and used it will enrich everyone’s overall perspective on the world’s embrace of the Internet and computers today.5% return on its trades. “the computer is maybe 80% to 85% accurate when analyzing text. including the military.” based in los angeles. to my mind. whereas micros were lonely islands of BASIC programmers and spreadsheet enthusiasts. built. and courseware. flat-panel displays sporting touch screens in 1972. not text. Illinois. analyst. “When you do longterm predictions. offers a similar perspective.S.” schumaker and chen tested AZFintext with five weeks of data from the fall of 2005. Over the years. “I loved Steve Levy’s Hackers: Heroes of the Computer Revolution. “I was amazed by the system and completely ignored the microcomputer revolution going on at the time because here was a computer that was all about connecting people. a true innovation and far ahead of its time. the conference’s primary organizer. and are analyzing not just traditional financial news outlets. and its impact is everywhere. an assistant professor of information systems at Iona college. chen expects AZFintext to be deployable for real-world trading in two to five years. Stock Market A pair of computer scientists has developed an artificial intelligence program that. the PLATO people?” Dear. schumaker.” Sheldon Hochheiser. current computer-aided quantitative funds analyze numerical data. which included more than 9. in simulated trading.” chen told The Wall Street Journal in a recent interview. “PLATO for years served as an excellent predictor for how the Internet would evolve. but where is volume two about the other heroes of the computer revolution— namely. but blogs and employee and investor forums. and used it will enrich everyone’s overall perspective on the world’s embrace of the internet and computers today. “Nobody else had that. titled The Friendly Orange Glow.” he says. In computing history. they realized a return in excess of 20%. built.” While the mainstream technical media focuses on the history of online communities largely through studying the birth of the Internet by way of ARPANET and its descendents. Kirk L. © 2010 aCM 0001-0782/10/0800 $10.000 news articles and 10 million stock prices.” says Donald Dear. AZFintext boasts 20 com municaTio nS o f T h e ac m an enormous computational advantage over a lone human analyst with its ability to scan large volumes of financial news and analyze the words in the text.00 “exploring the history of PLaTo and the wild story of the people who designed. the story of this educational computer system is little known outside of the circles of people who either directly used the system or helped to build it. “PLATO was ahead of everyone by years. corporations. and by several branches of the U.S. PLATO. worked on PLATO as a programmer.” One such alumnus is Marc Andreessen. says PLATO was far ahead of its time with gas-plasma. 5 3 | NO. analyzes the text of financial news in the same fashion as a Wall street analyst. who considers himself fortunate to be a product of that environment. Brian Dear. 8 amount of data. the system developed into a sophisticated. AZFintext “won’t be as accurate as an individual analyst. “Bitzer’s work was. AZFintext produced an 8.” chen said. and buying or shorting stocks it believes will increase by more than 1% in the next 20 minutes. “Exploring the history of PLATO and the wild story of the people who designed. whose descendents have spread far and wide. —Jack Rosenberger . and schumaker and chen’s program is unique in that it takes a human analyst’s approach of deciphering financial news.000 times the | AU g U ST 201 0 | VO l . schumaker and chen also used quantitative strategies to produce a stock portfolio and employed AZFintext to make trades. 10 minutes. is due later this year. began as a project at the University of Illinois at Urbana-Champaign and was eventually commercialized in the 1970s by Control Data Corporation. government. Invented by Bitzer in 1960. there are many variables. outperforms the standard & poor’s (s&p) 500 Index and six of the top 10 quantitative funds. and deserves far more credit than it has gotten. networked computing infrastructure consisting of smart terminals that could run games. Dear maintains that approach misses an extraordinary segment of the computer history timeline. In terms of its ability to analyze one news article. however.news mated Teaching Operation. or AZFintext. but it can read maybe 100.
  left. to Gilles Brassard.1145/1787234. 53 | N O. Joseph S. BCS’s Lovelace Medal was presented to John Reynolds. and Joseph S. in particular to the fields of sensor data fusion and of autonomous vehicle navigation. © 2010 aCM 0001-0782/10/0800 $10. of Communications. RSA Professor of Computer Science and Engineering at Massachusetts Institute of Technology and professor of computer science and mathematics at Weizmann Institute of Science. Gödel Prize In recognition of their outstanding papers in theoretical computer science.1787267 Jack Rosenberger Gödel Prize and other cS awards Sanjeev Arora. the British Computer Society. 8 | c om m u n ic aT ion S of T he acm 21 . Waterman award The U. the nation’s top medal for science and engineering. PHotoGra PH by ( rIGH t) tony sCarl ato s. an associate professor at New York University’s Courant Institute of Math- ematical Sciences. Hugh Francis DurrantWhyte. Brassard is one of the inventors of quantum cryptography and a pioneer in the field of quantum information science. T h e e u R o p e A n A s s o c I At I o n for Theoretical Computer Science (EATCS) and the ACM Special Interest Group on Algorithms and Computation Theory (SIGACT). Gödel Prize winners Sanjeev arora. National Science Foundation (NSF) selected of Subhash Khot. Khot works in the area of computational complexity and seeks to understand the power and limits of efficient computation. to receive the 2010 Alan T. Gerhard herzberg medal The Natural Sciences and Engineering Research Council of Canada bestowed the Gerhard Herzberg Canada Gold Medal. and other researchers are recognized for their contributions to computer science. Canada Research Chair in Quantum Information Processing at the Université de Montréal. Carnegie Mellon University in recognition of his work of the last four decades and his contribution to the theory of programming languages. A theoretical computer scientist. for their concurrent discovery of a polynomial-time approximation scheme for the Euclidean Traveling Salesman Problem. news.B. Royal Society fellows The 44 newly elected 2010 Fellows of the Royal Society include two computer scientists.S. for her fundamental contributions to the theoretical foundation of modern cryptography.news Milestones | DOI:10.B. alan T. was honored for his fundamental contributions to both artificial intelligence and database systems. a professor of computer science at Princeton University. director of the Australian Cen- ter for Field Robotics at the University of Sydney. was honored for his major contributions to robotics. Mitchell.00 AU g U ST 2 0 1 0 | VOl.B. a professor in the Department of Applied Mathematics and Statistics at the State University of New York at Stony Brook. ( leF t) F roM ItC s. EATCS and ACM SIGACT awarded the 2010 Gödel Prize to Sanjeev Arora. and Joseph S. Waterman Award. Considered the NSF’s most prestigious honorary award since its establishment in 1975. Georg Gottlob. a professor of computing science at the University of Oxford. it is given annually to an outstanding researcher under the age of 36 in any field of science and engineering supported by NSF. mitchell. Jack Rosenberger is senior editor. and other organizations recently honored select scientists for their contributions to computer science. tsInGH ua un IVersIt y Roger needham award and Lovelace medal The British Computer Society (BCS) presented the Roger Needham Award to Joël Ouaknine of the Oxford University Computing Laboratory in recognition of his seminal and mathematical contributions to the field of timed systems modeling and analysis. a professor at the School of Computer Science. Benjamin franklin medal The Franklin Institute presented the 2010 Benjamin Franklin Medal in Computer and Cognitive Science to Shafrira Goldwasser. Mitchell.
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  Internet policy. may be losing its leadership position in this key industry have spurred a series of governmental initiatives to address the problem. The stimulus package enacted during the initial days of the Obama administration dedicated $7. 8 . once ranked 4th among industrialized nations in the percentage of residents subscribing to broadband. but rather how and when.1145/1787234.S. Yoo economic and Business dimensions Is the Internet a maturing market? If so. Interestingly. The first is the relatively low level of U. The plan is designed not just to ensure that broadband is available and affordable to all Americans. but also to devise ways to address the fact that a surprising number of houseWo conceRns domInAte comm unicaTio nS o f Th e ac m T holds are not subscribing to broadband even when it is available. broadband adoption. Concerns that the U. markets follow the pattern predicted by product life cycle theory. management literature exists suggesting that both developments may simply reflect the ways the nature of competition and innovation can be expected to evolve as markets mature. product life cycle theory examines how the pattern of demand growth affects the nature of competition over time.v DOI:10. The predominant version posits that new product markets pass through four distinct stages shown in the prod- The real question is not if the nature of competition and innovation will change.S. this literature has the potential to provide new insights into how to craft broadband policy and what steps business managers might take to prepare for the future. Others are entering into strategic partnerships that allocate more bandwidth to certain sources and applications. Some are offering specialized services that guarantee higher levels of quality of service to those willing to pay for it.2 billion for new investments in broadband infrastructure. if not most. The second is the debate over network neutrality. If applicable to the Internet. A central feature of every leading marketing textbook. which the agency released to much fanfare this past March. Demand-Side considerations: Product Life cycle Theory The best-known theory of market maturation is known as the product life cycle.1787243 viewpoints Christopher S. Empirical research has confirmed that many. 5 3 | NO. 24 | AU gU ST 201 0 | VO l . it has currently slipped into 15th place. what does that imply? the current debates over U.S. Although the U. It also required the Federal Communications Commission to prepare a national broadband plan.S. Network providers are experimenting with a variety of new business arrangements.
  as the theory predicts. Supply-Side considerations: Dominant Design Theory A parallel line of research in this framework explores the supply-side of market maturation. firms typically offered a single product designed to appeal to the broadest possible audience. there is nothing surprising about the prevalence of offering a more complex array of services and price points. as technologically superior substitutes emerge.viewpoints ar Deve t in n pme lo t uct life cycle figure here. risk tolerant. this initial stage gives way to the growth stage. Instead. These firms are trying to increase revenue in their primary market and set themselves up to offer new services that generate more revenue. Apple. firms focus on finding ways to deliver greater value to customers who are already in the market. and Microsoft are becoming more aggressive about invading territory traditionally controlled by other leading firms. revenue growth no longer depends on attracting customers who IllustratIon by da rrel rees are not yet in the market. That also explains why industry leaders such as Yahoo. Over time. The nature of competition changes as the market advances from one stage to the next.S. data collected by the FCC suggests that the growth curve has passed the inflection point marking the transition from growth to maturity. the product’s novelty dictates that sales are small and grow relatively slowly. In order to keep production processes simple and to make the product easy for customers to understand. Price and quality took on greater importance. During the introduction stage of the broadband Internet during the mid-tolate 1990s firms focused on inducing early adopters to try the product. When one focuses solely on broadband. 53 | N O. as theory predicts. firms began to target the mass market and to compete to attract new customers who are not yet being served. It is a natural outgrowth of maturity and the natural increase in rivalry that results when firms compete in a market that is no longer growing as fast as it once did. during which sales grow rapidly. U. As the market transitioned into the growth phase. If a market for the new product develops. 8 | c om m u n ic aT ion S of T he acm . the product enters the decline stage. After enjoying an extended period of rapid growth. During the introduction stage. This focus in turn caused firms to emphasize cutting-edge tech- nological features and to deemphasize product quality and price. Internet penetration has leveled off at approximately 75%. Eventually. As the market enters the maturity phase. during which sales growth flattens. Internet usage over the last two decades fits comfortably into this pattern. and price insensitive. According to this theory. once again. Google. which describes the typical Internet user circa 15 years ago. Early adopters tend to be technologically sophisticated. Called dominant 25 AU g U ST 2 0 1 0 | VO l. market saturation causes the product to enter the maturity stage. there are some indications that the market is on the cusp of entering the maturity phase.
  see “Product life Cycle theory and the Maturation of the Internet. empirical research indicates that other patterns exist as well. Such measures would reinforce the obstacles to architectural innovation that already exist. built around TCP/ IP and its many extensions. Significance for internet Policy and Business Strategies The implications are myriad. Others condemn these theories as self-fulfilling prophecies. which provides little incentive to invest in advanced production processes. 5 3 | NO. Even if it is not always possible to anticipate precisely how the nature of competition and innovation will change. 26 com municaTio nS o f T h e acm | AU g U ST 201 0 | VO l . Applying market maturation theory to the Internet comes with a number of limitations. They suggest the new demands being placed on the network are creating the need for fundamentally different design architecture.upenn. At some point the basic product features and technological characteristics coalesce into a dominant design. The desire to provide greater value to customers is creating greater interest in facilitating content providers’ long-standing interest in monetizing content streams. they should look for indications that the market may be reaching saturation and plan for how their strategy and those of their customers and competitors are likely to change as these phase transformations occur. while key turning points are easy to identify in retrospect. Instead. that both will change over time is a given. This impetus toward certain trajectories becomes more pronounced if a technology is embedded in a web of interdependent technological processes. These technological trajectories frame the way each field determines which problems are worth solving and which technological solutions are likely to be the most promising. Moreover. Yoo (csyoo@law. sales introduction Growth maturity Decline time design theory. Innovation. suggesting that technological guideposts or paradigms emerge that direct research along particular avenues or trajectories. and Competition at the university of Pennsylvania. The presence of such a design hierarchy establishes a technical agenda that channels subsequent innovation along particular lines. it posits that when a technological breakthrough first occurs. Copyright held by author. Instead. they have proven quite challenging to anticipate far in advance. For a more extensive presentation of these ideas. And as this theory would predict. The real question is not if the nature of competition and innovation will change. but rather how and when. Any other approach risks precluding the industry from following its natural evolutionary path and rendering the obstacles to architectural innovation that already exist all but insuperable. The transformation of the Internet from an experimental testbed into a mass-market platform has made major architectural change more difficult. is several decades old. At the same time. Christopher S.” Northwestern University Law Review. 104:2 (forthcoming 2010). both to lower costs and to offer services targeted at particular subgroups of customers. just as product life cycle theory would predict.viewpoints The product life cycle. Other scholars have extended this analysis.edu) is Professor of law. Communication. Although the pattern of sales growth predicted by product life cycle theory is the most common. The flattening of revenue growth inevitably gives network providers incentive to experiment with increasingly specialized equipment. It also obstructs innovations that are inconsistent with the existing architecture and can delay or prevent new architectures from evolving. just as design hierarchy theory would predict. Innovation becomes less driven by trial and error and instead becomes more systematic and incremental. and engineering and director of the Center for technology. as their widespread acceptance leads firms to manage their products in ways that cause these patterns to come true. they should focus on creating regulatory structures that preserve industry participants’ freedom to experiment with new solutions and to adapt to changing market conditions. which leads some to question the theory’s generality. What does that have to do with the Internet? A growing number of technologists have noted the core architecture for the Internet. uncertainty fosters lack of product standardization. Business managers and IT professionals must not take for granted that the competitive dynamics and the technology underlying the industry today will still be in place tomorrow. This theory also suggests that policymakers should be careful not to lock the Internet into any particular architecture or to reflexively regard deviations from the status quo as inherently anticompetitive. they are finding that the standardization on a certain approach combined with the interconnected nature of the technologies comprising the architecture is limiting the Internet’s ability to evolve to meet these new demands. 8 . applying market maturation theory to the internet comes with a number of limitations. market maturation is causing firms to place greater emphasis on capturing a bigger fraction of the dollars that are available.
  a series of technological advances in computing has repeatedly reshaped the undergraduate computer science curriculum. and in conjunction with the growth of wireless networks.1145/1787234. from the nuts and bolts of network protocols to the social impacts of online communities.tH oMPson/Ca rneGIe Mel lo n egInnIng In the 1970s. has led to courses targeting smartphones and PDAs instead of conventional computers. Bill Gates drew a parallel between today’s robotics industry and the computing 27 AU g U ST 2 0 1 0 | VO l. Robotics is the leading candidate for the next dramatic change in the CS curriculum. And when inexpensive graphics processors and sound cards grew electronic gaming into a multibilliondollar business with revenues comparable to the film and music industries.a CS departments responded by introducing a variety of multidisciplinary courses in game design. Touretzky education preparing computer science students for the Robotics Revolution Robotics will inspire dramatic changes in the CS curriculum. In a 2007 Scientific American article.1787244 David S. 53 | N O. PHotoGra PH by et Ha n J. and led CS departments to introduce courses in computer graphics and HCI.com: motion pictures $33 billion. and power technologies are fueling an explosion in robotics com- parable to what microprocessors did for computing three decades ago. Advances in sensing. t Ira. produced new types of platforms that are always on and always with us.V B viewpoints DOI:10. The microprocessor that launched the personal and then wearable computer revolutions.9 art o evel in D ent pm calliope: a prototype create/aSuS robot with a pan/tilt camera and gripper arm. music $15 billion. 8 | c om m u n ic aT ion S of T he acm . a Estimated 2008 revenues from Hoovers. Affordable bitmapped displays brought GUI interfaces into widespread use. actuator. The maturation of networking technology that led to the Internet and the Web also spawned a whole spectrum of new courses. computer and electronic games $12 billion. gave us the new field of human-computer interaction.
  speech and gesture recognition) are core technologies. grasp and path planning.3 We see glimmers of our robotic future in today’s self-parking cars. Real robotics involves deep. underpowered. and flying devices ranging from micro-scale robot bees to the airliner-size Eitan UAV. and while loops. The second impediment to be overcome is the lack of suitable robot platforms for undergraduate instruction. the Nao will remain out of reach for most educators. but they can be made accessible to undergraduates. Who in 1971 would have looked at the first Intel microprocessor and predicted eBay. Penbo from Bossa Nova Robotics. and that market niche has yet to be filled. The public doesn’t always appreciate that the elaborate hardware platforms students construct must be primarily teleoperated because students aren’t being taught the kind of software that would allow their robots to act autonomously. The time to do that is now. and human-robot interaction (face tracking. limited but intriguing toys (Wowee’s Robosapien. On the other hand. or “sexting”? impediments to Progress We can help speed the revolution by introducing our undergraduates to state-of-the-art robotics hardware and software. kinematics calculations. probabilistic localization and navigation. Robotics cannot be taught in CS1. computationally demanding algorithms. Product Refinement 2010 Technology maturity Laptops Smartphones Quantum computing educational robots Time Since introduction Real robotics involves deep. Robotis Bioloid). the AIBO had not yet caught on as a teaching platform. They’re right. and multiple IR range finders and accelerometers). this is not the same as teaching them robotics.2 He compared today’s state-ofthe-art industrial robots—priced at tens to hundreds of thousands of dollars—to 1970s era mainframes. more than 40 nations now have military robotics programs. and one astonishingly successful vacuum cleaner: the Roomba. are another source of misconceptions. Machine vision. The first is misconceptions held by some about the nature of the subject.8 CS educators must understand that while it might be a good idea to use simple robots to teach students about variables. 8 . Dobbs’ Journal once nurtured amateur computing enthusiasts.000 price tag was comparable to high-end laptops of its day. The use of simple robots to teach basic programming concepts dates back to Papert’s Logo turtle of the 1970s5 and Pattis’ Karel the (simulated) Robot in the 1980s. and of interest mainly to hobbyists who enjoy tinkering with technology for its own sake. Today these are found mainly in advanced research labs and graduatelevel robotics courses.net. while the popular magazines Robot and Servo are energizing the robotics hobbyist community the way Byte and Dr. But when Sony abruptly exited the robotics market in 2006. which emphasize the mechanical engineering aspects of the field at the expense of computer science. VEX Pro. A few schools are now teaching robotics courses using Naos. 5 3 | NO. multirobot coordination. while consumer robots resemble 1970s microcomputers: crude. but it will be a while before the economies of mass production can do for AIBO. Meanwhile. High school robotics contests such as US FIRST. Advances in robotics are reported weekly at technology news sites such as Robots. computationally demanding algorithms. many more in Japan). rich sensor suite (including a color camera. The AIBO’s $2. procedure calls.1 and a variant of Alice (http:// www. Meanwhile. Google Earth. Pleo from Innvo Labs.viewpoints industry at the start of the PC revolution. But three factors have stymied progress in robotics education for Technology maturation curve. but at a retail cost of approximately $16.4 More recent examples include a Python-based programming course using the Parallax Scribbler.000. and sophisticated servos with position and force feedback. Mindstorms’ widespread and growing use in high schools and 28 communicaT io nS o f T h e ac m | AU g U ST 201 0 | VO l . But the robotics revolution will be farther ranging—and a lot more weird— than most of us can envision now. Today’s consumer robots include a variety of kits (Lego Mindstorms. The devices used in CS1 courses typically have no camera and can’t even drive in a straight line without drifting. The Lego Mindstorms kits used in many current college courses are no better. which oversees robotic soccer competitions worldwide. cameras that recognize human smiles. any more than making a penguin move around in Alice counts as teaching computer graphics. the groundbreaking Sony AIBO robot dog was an excellent instructional platform due to its powerful MIPS processor.alice.or Nao-type robots what they’ve already done for laptops and smartphones. In 2007 the RoboCup Federation. more than five million Roombas have been sold. Wikipedia. There are some who believe that educational robots should cost no more than a Lego Mindstorms kit: only a few hundred dollars.org) that can both simulate an iRobot Create and teleoperate a real one via a bluetooth dongle. selected the Nao humanoid from Aldebaran Robotics to replace the AIBO in the Standard Platform League. stereo microphones. and a dozen others. computer scientists.
  Scientific American (Jan. polymorphism. and Tekkotsu (. 6. 2010). 2 (Feb. 3.tekkotsu. 8 | c om m u n ic aT ion S of T he acm 29 . 4 (apr. Player/Stage and ROS have similar philosophies. not low-level details of rendering algorithms or GPU programming. research funded by national science Foundation award due-0717705. Other groups are developing Tekkotsu support for additional platforms. logo. Google earth. C. and curriculum. ACM 52. while the laptop provides a Webcam for vision.org). and anderson. Both support a wide variety of platforms and devices.org). navigation. 2009). Second Edition.J. where the focus is on principles of visual aesthetics or the graphical presentation of information. For just a few more years. computer scientists will build their own platforms for education and research. 2008). Early graphics programming was done by turning pixels on and off.edu) is a research professor in the Computer science department and the Center for the neural basis of Cognition at Carnegie Mellon university in Pittsburgh.s. a12. d. or. e. new york. multiple inheritance. alice and robotics in introductory Cs courses. He was named a distinguished scientist by aCM in 2006. 98–102. Pattis. 2010. et al. In Proceedings of the Fifth Richard Tapia Celebration of Diversity in Computing Conference (Portland. 8. Modules can be written in any of several languages. But graphics has developed into a wonderfully rich field that includes specialties such as Web design. 5.b have found a good solution by mounting a laptop or netbook atop an iRobot Create. They need robots that can see. and plenty of computing power. In Proceedings of the AAAI Symposium on Educational Advances in Artificial Intelligence (eaaI-10). Both provide a general communication framework for a collection of indepenb Jeff Forbes at Duke University. davis. It offers a common representation scheme for vision. 58–65. and high-level frameworks for robot instruction will enable robotics application development by a diverse population of users and innovators. a robot in every home. 4. (atlanta. or purchase a pre-assembled version from a commercial vendor. and Constructionist learning. t.S. 2009). IEEE Pervasive Computing 7. And both are designed primarily for research. for the same reason that no individual today builds their own laptop or cellphone. 66–72. But for all three frameworks. dual-coding representations for robot vision in tekkotsu. But since highly capable robots are not yet mass-produced consumer products. Papert. In less than a decade this will become infeasible. educational robotics is entering the unstable region of the technology maturation curve. instead it provides well-tuned primitives for a small number of educational platforms. J. Wiley. and tira-thompson.net). Better algorithms for perception and manipulation. b. AU g U ST 2 0 1 0 | VO l. with processors that can run the sophisticated algorithms computer scientists should be studying. 5–9. look at the history of graphics software. the tekkotsu “crew”: teaching robot programming at a higher level. although Player/Stage in particular has been widely used for education. b. References 1. or “sexting.6. That will be one unmistakable sign that the robotics revolution has arrived. 53 | N O.viewpoints even middle schools underscores my point that undergraduates require something better. Israeli robots remake battlefield.org/Create. takes a different approach. 1995.ros. developed with Ethan Tira-Thompson in my lab at Carnegie Mellon University. Chad Jenkins at Brown University. including the AIBO and the Create. a WiFi connection. et al. Several colleagues in the U. The three major open source frameworks for robotics application development are Player/Stage (http:// playerstage. 2007). The Create—a Roomba without the vacuum—provides an inexpensive mobile base with a few simple sensors. can find all the necessary information at http:// www. Anyone who thinks these platforms are too expensive should recall what schools were paying for workstations a few years ago. 2010). Commun. Computer science in the conceptual age. Autonomous Robots 22. Touretzky (dst@cs. some of whose job descriptions are as unforeseeable today as “Web designer” was in 1971.com. Web and game designers rely on computer scientists for the tools of their trade. The final impediment to be overcome is the lack of easy-to-use software. software.e. 9. Wellman. The Wall Street Journal (Jan. 7. Pa. 2007). Wikipedia.” dent software modules responsible for controlling various types of hardware or providing services such as localization. including the Nao and various robot arms. game design. r. a speaker. Georgia. Who in 1971 would have looked at the first intel microprocessor and predicted eBay.7 The idea is to provide a unified framework that undergraduates can master in two-thirds of a semester and then move on to working on an interesting final project. Zyda. and Zach Dodds at Harvey Mudd College have been at the forefront of this work. Copyright held by author. balch.cmu. As illustrated in the figure on the preceding page. Let’s get started. 12. Tekkotsu does not strive for universal hardware coverage. An enhanced version with a pan/tilt camera and an arm with gripper is presently under development (see the image on the first page of this column).. touretzky. 2. The total parts cost can be as low as $600. Monica Anderson at the University of Alabama. and manipulation tasks. touretzky. the frameworks themselves make no assumptions about representation. Readers who would like to put one of these robots together themselves. It is implemented in C++ and makes heavy use of abstraction facilities such as templates. and scientific visualization. I believe our notions about robot programming will likewise broaden in the coming years. and namespaces. solomon. 425–435. functors.sourceforge. more work remains to be done to make advanced robotics technologies easy for non-experts to use. Karel the Robot: A Gentle Introduction to the Art of Programming. Our students will create the technologies that make this possible. 12 (dec. but they have different skill sets and are not themselves computer scientists.. ROS (. levinson. d. July 13–14. designing personal robots for education: Hardware. today’s educators must innovate..wikispaces. David S.. our Robotic future To predict the future of robot software. M. another approach Tekkotsu. The applications of computer graphics have outgrown the confines of a single discipline.s. just as early robot programming was done by turning motors on and off. Gates. M. C.
  by 2007. and Golden Customs. An assessment of the relative achievements in IT infrastructure. China was already the world’s largest mobile telecommunications market. The most recent figures indicate the number of fixed-line subscribers had reached more than 310 million. e-commerce. When China started economic reform in the early 1980s. which had 270 million subscribers and an 11% growth rate. but is it also emerging as an IT superpower? Certainly it has gone a long way toward catching up and even leading in some fields. 99. respectively. China had the world’s largest population of Internet users (more than 300 million) and the largest population of broadband users (more than 100 million).1145/1787234.1 Even in the 1990s in Beijing. 8 PHotoGra PH by IM aGIneCHIna VIa a P IMaGes . China has also pushed ahead with national informatization programs initiated in 1994 with the creation of the National Information Infrastructure Steering Committee.6 understanding catch-up IT infrastructure and services. These are now just one small part of an overall drive for e-business. But—as recent difficulties with Google illustrate—it must also address ongoing challenges before the superpower label can be applied. As Fortune 500-listed companies. | AU gU ST 201 0 | VO l . 5 3 | NO. Annual trade in China’s B2C market. By 2001.000 citizens. and a 19% annual growth rate during the 2000s. mobile Internet connectivity. and e-government that has created more than 100 national information systems that provide a true “digital economy” infrastructure.S.000 citizens.V C viewpoints DOI:10.. The latest figures show more than 640 million subscribers in 2008. or Japan with 110 million subscribers and a 5% growth rate. or 230 per 1. the Chinese mainland had just four telephones per 1. and are now adopting 3G technology. From that point. and innovation in China. for example.5% of all administrative villages were connected to the telecommunications infrastructure. This launched various “Golden” projects such as Golden Bridge. China’s mobile telecommunications networks upgraded to GPRS and EDGE. the three operators own nationwide networks and provide value-added services. its information and communications infrastructure was weak. Golden Card. and linked customs points through a national EDI system. But the 2004 Village Access project ensured that. constructed a national credit card network.7 The mobile telecommunications market has similarly gained rapid momentum since 2G digital systems were 30 comm unicaTio nS o f Th e acm internet users in china. During this period. which have built a national platform for providing commercial Internet services. though. We can understand its “techno-nationalism” as the foundation.000 population. just over the border in Hong Kong—still a British colony at that time—there were approximately 460 phones per 1. In contrast. For a long time that population was restricted to large cities and coastal provinces. In 1980. firms.to three-year wait was required to have a telephone line installed in a typical household. a combination of very strong demand. All of this has been built around a fast-growing e-infrastructure: by 2009. heavy state investment plus supplyside support from government to the monopoly supplier ensured a major change. deployed in 1994.5 Contrast this with the U.1787245 Ping Gao and Jiang Yu emerging markets has china caught up in It? h I n A I s e m e Rg I n g as a new economic superpower. and the like. is now around $3 billion (total e-commerce is approximately 100 times greater) and is growing at a rate of about 50% per year. a two.
  China Mobile purchased Pakistan’s Paktel and used this as the launching pad for its own international brand. Considering relative growth rates. China’s TD-SCDMA now competes with W-CDMA (originating from Japan and Europe) and CDMA2000 (originating from the U. terminals. but maintained its sales group and R&D functions in mainland China and has not closed its site in China. The TD-SCDMA standard is widely used in China but is also starting to experience international deployments: first in Ghana but also 31 Some chinese iT firms have evolved from this domestic platform to innovate enough to compete globally. and steering local demand by buying locally innovated products. Google relocated part of its search services under the domain name Google.com is the global leader in the B2B market with 47 million users covering virtually every country in the world. local firms are the dominant force in the domestic market. before the 1990s China mainly depended on foreign technology.). in areas such as PCs and consumer electronics. This has seen international strategic alliances set up between China Mobile and Vodafone.4 reflecting the broader globalization of Chinese telecommunications firms. it has pushed to have Chinese-developed standards recognized and used. for example. such firms often create local joint ventures that help develop local partners. it has had some success in breaking beyond the confines of the domestic market. In 2006. spending some 10% of revenue on R&D centers based not just in China but now in India. Some Chinese IT firms have evolved from this domestic platform to innovate enough to compete globally. though. The quality and utilization of such patents outside China is sometimes limited. like Amazon and other major Internet firms. In the early 1980s. Initially a sign of weakness. 53 | N O. In just two decades. Some firms have been able to grow even further. Understanding the importance of standards in the internationalization of IT. It is the single largest applicant under the international Patent Cooperation Treaty. Perhaps most notable has been the performance of Lenovo and Huawei.3 Huawei achieved a significant milestone in 2009 when it won 4G roll-out contracts in Norway and Sweden that beat rivals Nokia and Ericsson in their home markets. nearly all leading IT firms have a joint venture or foreign independent investment operation in China. Today.—and the country is no longer the world leader.viewpoints Of course. China has managed these relationships. 8 | c om m u n ic aT ion S of T he acm . Take relative figures—for example. technology. Its 2007 $1.000 employees and worldwide sales of more than $21 billion covering mobile.2 That rating reflected Huawei’s relentless investment in technology R&D. Chinese technology dominates the domestic market. Lenovo achieved global attention and reach through its 2005 purchase of IBM’s PC division. From being a stunted consumer market. Amazon. set up in the 1980s. with the world’s biggest mobile subscriber base. China’s Alibaba.cn to Hong Kong.” IT firms. And ambitions have gone beyond just alliance: in 2007.. This purchase was an iconic statement of changing fortunes that led the firm— still one-quarter-owned by the Chinese government—to be the world’s fourthlargest PC maker in 2009 with approximately $15 billion in sales. was thus forced to look to foreign partners. and value-added services. it has not just caught up.7 billion IPO was the largest for any Internet firm since Google. and China Unicom with Spain’s Telefónica. BusinessWeek rated it one of the world’s 25 most influential AU g U ST 2 0 1 0 | VO l.S.S. Huawei can again provide an illustrative example: FastCompany rated it among the world’s top five most innovative companies in 2010. (At the time this column was written. has over 500 million registered users and a 78% share in the instant messaging market. Europe. along with Facebook.” And taking into account the availability of services and standards then at least for a significant proportion of China’s population. It companies in 2008. Construction of the nation’s IT infrastructure has been predominantly based on indigenous products.S. has set up in China. but in some areas taken over. and expertise has acted as an impetus rather than a restraint to local firms. its manufacturing industries were poor in both quality and innovation. Government has also played a role: through investment and policy decisions China has moved to sixth in the global patents league table.S. when China was first targeting IT. 48% mobile device penetration compared to 87% in the U. In IT services. It is the world’s number-two firm in telecommunications equipment and number one in subfields such as mobile switches and next-generation network technology. the message is “already caught up.) Foreign firms have also been important in IT manufacturing. including mobile systems and computers. China will win most absolute IT numbers counts because it has the world’s largest population. China has grown to be one of the world’s largest producers of IT equipment. Google. The Financial Times ranked it fifth in a 2007 list of the world’s most valuable brands. ZONG. China Mobile became the world’s largest mobile operator. and the U. networks. and ensured the large influx of foreign capital.000 of capital distributing imported telephone exchanges. By 2009. but the Chinese government is also playing a higher-level game. but catching up. In this endeavor. Since then the nexus of government and Chinese firms has adopted a twin-track approach to creating domestic technologies: boosting supply by investing in R&D. Indigenous manufacturers have become key international players. Shenzhen-based Tencent. As noted earlier. Huawei’s rise has been even more dramatic given its beginnings with a staff of 14 and some $3. 6% broadband penetration compared to 23% in the U. and Google. As a result. Apple. it had 90. IT innovation. one should modify that to “catching up quickly. The International Telecommunication Union has ratified three main 3G standards based on CDMA. with imported technology dominating.
  local capacity was too limited and risked stunting wider growth. BusinessWeek (aug. Indeed. less than three decades ago. beijing. 8 . 8. But Google’s reaction of pulling in U. China’s relations with foreign IT firms have been volatile. Gibson.com/ss/08/12/1211_ most_influential/index. How did this happen in a country that.manchester.viewpoints planned for South Korea and some Eastern European countries. 2010. One-quarter of U. Chinese academy of sciences.ac. So has its large size. partnered. government assistance is not unusual. and McGregor. 5 3 | NO. Together. and the greatest support to local innovation. infrastructure was very weak in the 1980s but there was some local capacity.businessweek. China Telecommunications Over 50 Years.. The Chinese government has also created and supported a series of R&D programs that bring firms. (Mar. A few IT firms and technologies are now world-leading. In sum.” This was made possible due to what had already been achieved since the 1980s.manchester. and Centre for development Informatics. Tight governmental control and censorship of information..uk/cdi. Government therefore opened the market to foreign firms in 1982.uk) is a lecturer in development informatics at the Institute for development Policy and Management. But it faces three challenges.fastcompany. for example. 38–39 Ping Gao (ping. Global brands. J. Ministry of Industry and Information technology. 28. (Feb. and tolerated— often simultaneously—all in a short time span.ft. But government and its policy of “technonationalism” has been a significant influencing factor with a series of policies that made IT—especially local IT capacity—a priority. China is catching up quickly. even though this may be against the firm’s own economic interests and wishes. Congressional countermeasures are increasing. The general approach has been heavy control followed by liberalization. this may damage foreign trade and investment and. China. beijing. The Chinese government decided to retain the state monopoly and granted it tax and investment privileges. Jiang Yu (yujiang@mail. gov. Together with fallout from the Google case. and universities together to work on R&D for key technologies.casipm. sometimes vice versa. in telecommunications services. Creation of the TD-SCDMA standard involved just such a consortium. Its national policies. Google is somewhat unusual— China does not rely on it (the Chinese firm Baidu dominates the search market) and Google does not rely on China (revenue from within China represents approximately 1% of total). Copyright held by author. hacked. and stewart. Ministry Report News. sed. harm innovation in China.S. For example.. Wray. 1999. the state and business. Western Europe. beijing. ac. He is the editor of the Journal of Science and Technology Policy in China. research institutes.. Financial Times. Indigenous innovation also faces challenges from overseas. 2010).html 8. China must hope these future large-scale initiatives do not lead it to slip off the high-wire arrangement it has constructed. the world’s most influential companies. In telecommunications equipment. It used the lure of China’s 1. explaining catch-up We answer the question posed in the headline for this column with a mixed but generally positive response. high-tech firms feel they are losing out due to the 2006 Plan. Geneva. as such. H. And.htm 7. But governments may push the wrong way. and neighbors like Japan and South Korea. Thirdly.S. http:// www. Western business struggles to break Chinese barriers.S. For example.gao@manchester. The Observer. Indicators/Indicators. More difficult will be China’s aim for innovation leadership through techno-nationalism. media.gov. london. and whether this standard will truly succeed internationally. university of Manchester. International telecommunication union.8 Accusations of Chinese protectionism and calls for U.K. | AU gU ST 201 0 | VO l . References 1. u. China is still some way 32 communicaT io nS o f T h e acm behind the U. will no doubt allow the “catching up quickly” to continue. was decidedly “Third World”? China’s general economic growth has helped. it was desirable because of what had yet to be achieved. ICT-Eye. criticized. Only time will validate whether it was right to override other voices.S. Sometimes they seem needed but not wanted. with major national initiatives already under way in the areas of nano-electronics and 4G mobile networking. 2007. Central Government of the People’s republic of China. though. as an important propaganda channel.3 billion potential consumers as leverage to encourage Western firms to compete among themselves in offering the best technology transfer to China.cn/n11293472/n11293832/ n11294132/n12858447/12985105. r.itu. Its current model will remain central to ongoing IT catch-up and leadership. it forced China Mobile to deploy the TD-SCDMA standard. Plan-based indigenous in- novation requires direction from government. 2.cn) is an associate professor in the Institute of Policy and Management. Google. Sometimes they are attacked in private but soothed in public. 2008). has been welcomed. the world’s most innovative companies. Fast Company.uk/idpm/. these initiatives and actions mean China now has a drastically improved national innovation system.com/reports/globalbrands2007 5. the “Great Leap Forward” leitmotif in China’s history is one that not just encourages this type of “big push” approach. The Chinese government’s attempt to have indigenous WLAN Authentication and Privacy technology replace Wi-Fi in the local market did not succeed. e. the changes since the 1980s mean China’s techno-nationalism is now a high-wire act—balancing between the economic and the political. China has invested extensively in higher education over the next few years. coinciding with cutbacks in many Western nations. challenges and future Trends In IT infrastructure and services penetration.htm 4. broadcast networks cannot converge with telecommunications and Internet networks to offer new information services. 2009. 2010). Ministry of Information Industry.miit. In some areas of IT services and innovation it has caught up.. the global and the local. the broadcasting sector is tightly controlled by the state. In IT infrastructure. One focus of the 2006 15-year Science and Technology Plan is building “indigenous innovation.ac.ac. moving from monopoly to duopoly in 1994. and then opening to further competition in 1998 and 2008. Telecommunication Industry Statistics. and the Internet in the name of national security inhibits innovation. it shows it is required for development. 2008. hence. Only as the market grew was competition introduced to boost growth... sometimes vice versa.aspx 6. For example. mic/2010 3. but varied from sector to sector.
  ” or even “what” and “how.org George V. and I got the short one. Unless you are very good at giving presentations. I’ve been asked to make a presentation on the project my team has been working on for the past year. then it is far more likely your presentation will go over well. 53 | N O. from the abstract to the specific. I realize many people will say. the specific details—but also the “how. you need to know your material backward and forward before trying to explain it to a large group. no matter how technical. Other than trying to imagine my audience in their underwear—a piece of advice I have now been given at least five times—what would you suggest? Stage frightened I am almost positive that “Imagine your audience in their underwear” is just about the worst piece of advice anyone has ever given to a prospective speaker. What the best speakers are able to communicate is not just the “what” of a system—that is. Dear kV. I wasn’t really asked so much: the eight of us drew straws.acm. I have a nontechnical question for you. Actually. wants to listen to someone drone on about the low-level details of some system. Neville-Neil Kode Vicious presenting your project The what. 8 | c om m u n ic aT ion S of T he acm . the how. which. the “why. You might be an expert in the nitty-gritty details of the system you’re describing. Many people write presentations by starting with a title slide and then adding one slide after another until they feel they have enough to cover the material. but that’s not good enough—in fact. viewpoints DOI:10. Presentations full of only “what. No one. and here is why it’s built that way.” usually put audiences to sleep. Instead.V Dear Stage. “But that’s obvious. all different. here is how it works. and from what you say above you’re probably not. and most importantly.” The most memorable presentations are the ones that succeed on all three levels: “Here is what the system does. as Tom Lehrer has pointed out. is the Boy Scout marching song.1787247 Article development led by queue. and the why of giving an effective presentation. In preparing a presentation you should start with an outline.” but it turns out it’s not. 33 PHotoGra PH by sH enG Ha n AU g U ST 2 0 1 0 | VO l. You need not only to know the low-level details but also to be able to talk about the system you are describing at many different levels. Writing a presentation in this way inevitably leads to a wandering style of presentation that is more like a tortured walk through a maze of twisty paths. The most important step is to be prepared. there are practical steps you can take in order to ensure your presentation is well received.” If you keep these three questions in your head while writing your outline and slides.1145/1787234.” which is a higher-level description. it can be a drawback.
  Most audiences are literate enough to read your slides. spoke to the class. particularly in Asia.acm. When someone does ask a question. and then go back later and edit out the things that don’t work. and encourages your comments. | AU g U ST 201 0 | VO l . Put everything you can think of in as a potential slide title. leave out the details.org) is the proprietor of neville-neil Consulting and a member of the aCM Queue editorial board. The slides should act as a prompt for you to explain the what. 5 3 | NO. Some audi- ences. rather than because they are interested in the answer. Georg Petschnigg. Now that you have your slides together. believe it or not. He works on networking and operating systems code for fun and profit. You may also find there are people who are asking questions in order to prove how smart they are. Make sure to introduce each point. Very few one-slide presentations are effective. it must be used sparingly. presentation. actually read it.org/detail. advice: Eat lightly before your talk and make sure to use the bathroom. whether you think you need to or not. whiteboard. then stop asking and wait until the end of the presentation. friend. most people do well with two minutes per slide. Finally. It’s important to pace yourself as you speak. I can tell you that I tried increasingly high levels of caffeine to keep myself awake. you don’t have to do it for them. and I’d like to talk about that after the presentation. If you call for questions two or three times and receive no response. Many people practice their presentations in front of a mirror. and something that new speakers can actually forget to do. then it had better be the most interesting slide that has ever existed. which includes sections for Introduction. Maneesh Agrawala. Panting at the end of each slide is a good indication that you ought to be breathing a bit more. a piece of very basic. If you put up one slide and then speak for an hour.” After a few such rebuffs they usually quiet down. kV Related articles on queue. 34 communicaT io nS o f T h e ac m a presentation should not be a one-way broadcasting of information but rather a conversation between the speaker and the audience. If you have one of these people in your audience. do not ask questions during a presentation but only at breaks or after the presentation. Some people are able to make things up as they go along. or other visual aid. quips. You are telling the audience a story.cfm?id=1483108 George V. You should think of your outline as a way to brainstorm on the presentation. You need to pick three to five important points. or why of some point. the reason for two minutes per slide is to keep the audience paying attention. then do not try to make it up as you go along. The person asking the question is very likely facing you. it’s time to go over a few important points about actually giving the presentation. neville-neil (kv@acm. Do not speak in a monotone. and why before moving on to the next point. When speaking in public it is important to remember you are trying to engage the audience. I recommend avoiding torturing your significant other with your presentation unless he or she is also involved in the project. 8 . Many speakers like to ask for questions from the audience throughout the talk. “That’s very interesting. and code snips pertaining to his Communications column. If at some point during the presentation you find yourself writing on a chalkboard. If you don’t know the answer to a question. cfm?id=1166263 Code Spelunking Redux George V. Make sure each point covers the what. or loved one. how.org Comparing and Managing Multiple Versions of Slide Presentations Steven M. Drucker. and I always end with a Questions slide. or even their tenth. and make those important points the foci of the internal sections of the talk. simply say. and Conclusion. how. I have found that. or a very kind colleague. History. When you first display a slide people will. and don’t read the slides to the audience. make sure to repeat the question. if you are flipping slides every 15 to 30 seconds you will lose your audience’s attention. Even having just that much initial structure will help you to focus your thoughts on what you’re trying to communicate to your audience. depending on how much time you have allotted to present your material.acm. Although some people speak very quickly—in fact. if ever. it is not sufficient. in part to keep the audience awake but also as a way of pacing themselves. the points are not supposed to be surprises you foist upon the audience at the end of each section. on average. do not speak to the board. before you enter the room and begin your presentation.acm. Conversely. It is always easier to cut material at the last minute than it is to create something new. A presentation should not be a one-way broadcasting of information but rather a conversation between the speaker and the audience. and it’s your responsibility to keep the audience involved throughout the entire talk. but this is not what I’d recommend for someone doing their first. teaches courses on various programming-related subjects. unless you’re presenting to a group of fewer than 10 people in a conference room. I know an excellent speaker whose talk was once described as “being shot with a machine gun”—and others quite slowly. Remembering to breathe is quite important. There are few things more annoying than having the speaker whine about how no one is asking questions. he barely.org/detail_video. and perhaps base. While the “Any questions?” tactic can be useful.viewpoints I have a template for my presentations. Copyright held by author. and not the audience. Neville-Neil. and as such you should try to be engaging and to keep the audience interested. but no matter how much I took I could never remain awake through the full hour. One of my professors in college would stand at the chalkboard and read the textbook to it while writing out notes on the board. One common issue all novice speakers have is figuring out how long the final presentation will run. but they are not lines on a teleprompter for you to read. Although this is necessary boilerplate.
  1145/1787234. and Atari systems.b later incorporated these ideas into his novel.c a Personnel communication.. including “Virus” by E. and some marriages). email. Amiga. 1997. and more). disasters. d See Communications of the ACM 19. nnIVeRsARIes pResent An opportunity to reflect. some marriages). Next year is the 10th anniversary of its conceptual descendent. Spafford privacy and security Remembrances of things pest Recalling malware milestones.V A viewpoints DOI:10. When HARLIE Was One.H. deploying alteration of OS functions. Some malware applied vendor software patches to prevent other malware 35 AU g U ST 2 0 1 0 | VO l.1787246 Eugene H. and self-modification to foil pattern-based detection. which affected hundreds of thousands of Windows systems worldwide in less than 30 minutes. Denning and P. graduations. 1989) for several analyses and views. and other network services. “Blended” threats were common. Nimda. involving computer code and a corresponding vaccine program. and sometimes we grieve (deaths. Eds.a Benford’s friend. a few score viruses existed for other systems. or Pakistani). D. including the Macintosh. Addison-Wesley. By 2005. malware existed that spread by Web pages. c Early history of computer viruses can be found in many references. including components spread by inadvertent user activation. IllustratIon by Gordon stud er ˲˲ Last November was the 21st anniversary of the Internet Wormd that brought malicious software (malware) to the fore after it spread in part of the early Internet over several days. ˲˲ Next year is the 25th anniversary of the first widespread PC (MS-DOS) computer virus (known as Brain. Malware developers quickly overcame new defenses as they were devised. b David Gerrold is perhaps best known to many as the author of The Trouble With Tribbles story that was made into a much-beloved “Star Trek” episode. Consider: ˲˲ The first use of the term “computer virus. David Gerrold. Spafford in Internet Besieged: Countering Cyberspace Scofflaws. 8 | c om m u n ic aT ion S of T he acm . later confirmed in a letter to the editor of the New York Times. Denning.000 families (code variations) of viruses for Microsoft-based operating systems. By 2000 there were 40.” occurred 40 years ago in Venture Magazine. There are also anniversaries when we compare what might have been against what has actually happened (all the above. 1 (Jan. in a science fiction story by Gregory Benford. Sometimes we celebrate anniversaries (birthdays. published in 1994. 53 | N O. Lahore. code to disable security mechanisms and antivirus programs.
  supporting military actions against the country of Georgia. Milieu. and equate penetration efforts with security assurance. Early malware was developed for bragging rights or out of curiosity. see http:// www. The economics of security need to be changed.e although it is impossible to get a precise count because of their often-polymorphic nature: a “new” version is created each time a download occurs. ˲˲ Law enforcement has not been given sufficient resources. and some botnets whose origins cannot be traced may include millions of compromised hosts (for example. This includes increasing our understanding of the long-term risks and cost-effectiveness of security-related choices to enable better choices by system owners and operators. ˲˲ Research has been funded mostly to respond to current threats rather than to devise disruptive but safer replacements for current systems.com/threatlevel/2010/02/ apt-hacks/). global marketplace have led to numerous. public “computing health” organizations should be created: contaminated clients are a threat to the community as a whole. How did this happen? And what can we do about it? factors In no particular order. run everywhere” attacks. John Thompson. Although not without their own problems. obtain identity and account data. ˲˲ The market often rewards first-tosell and lowest cost rather than extra time and care in development. leading to a culture of “add-ons” for security and skewed expectations. but these have larger attack surfaces and more options to misconfigure and misunderstand. ˲˲ Vendors pursue upgrades and new releases as a means of maintaining revenue streams. and steal proprietary commercial information. Too many people believe narrow “secure programming”f approaches are the solution. Phishing. Globally. 8 . all-in-one products to minimize development and marketing costs. and unwary. Conficker). The public is beginning to realize what specialists have known for years: these problems are getting worse. Changes to liability protections for vendors. support. including political action in Estonia. that malware performed better at maintaining systems than their owners! Malware now includes “social engineering” components to entice the careless. Where private owners cannot afford necessary upgrades or services to “disinfect” and reconfigure their systems. unprotected. ˲˲ Customers in industry and government have placed more emphasis on acquisition cost than on total cost of operation. risk. Economics. botnets. Of those. distribute spam email. open standards to improve portability. including inadequate testing. ˲˲ The end user is burdened with the f “Secure programming” is writing code without certain features that have been frequently exploited. Well-established security principles are ignored— if the developers even knew about them. and John Viega. or prioritization to pursue malware authors and operators. and spying on human rights activists and the Dali Lama. and quality. The public needs basic education about good security and privacy practices to make better-informed choices. early malware was developed for bragging rights or out of curiosity. ˲˲ Feature lock-in (product and training compatibility) coupled with a lack of good metrics on security and safety have hindered innovation and competition. only a fraction is detected because of built-in stealth techniques and poor security practices by the victims. detection indefinitely (the APT or Advanced Persistent Threat. today’s malware is often written by criminals. but backward-compatibility and new features both contribute to new vulnerabilities.viewpoints from displacing it: ironically. 36 comm unicaTio nS o f Th e ac m | AU gU ST 201 0 | VO l . ˲˲ Vendors favor producing large. There have been many notorious uses of malware. and reexamining those parts of regulatory and intellectual property regimes that interfere with research and (re)use of sound security features. some of the most notable factors contributing to the proliferation of malware have included: ˲˲ Software is usually produced using error-prone tools and methods. and end users could also encourage more proactive actions by all involved. cross-site scripting and SQL injection have become commonly known terms. ˲˲ Insufficient diversity enables “write-once. Remediation We can reduce the malware problem by actions on four major fronts. Judicious use of rewards and penalties for product quality might help. unauthorized copies that may be ineligible for patches. reducing the barriers to competition that might lead to safer products such as by embracing vendor-neutral. annual losses from malware may total in the tens of billions of dollars (or more)—and how do we put a price on the loss of national defense information. or the safety of activists opposed to oppressive regimes? Tens of thousands of new instances of malware appear daily. some uses of virtualization and software as a service (SaaS) present opportunities for migration of end users away from poorly maintained systems. The science fiction story of 40 years ago is now a scourge causing huge global losses and evolving as a new tool of organized aggression. and whose operators cannot afford security add-ons.wired. Current malware may remain without e Personal communications from Vesselin Bontchev. costs and responsibilities for dealing with malware. ˲˲ Periodic software patching and production use of beta products are viewed as the norm rather than as unusual exceptions. today’s malware is often written by criminals—including organized crime—to commit fraud. 5 3 | NO. ISPs. and ˲˲ Issues involving pricing and licensing software in a diverse. including some posted online for anyone to use. Malware-generation tools have proliferated.
  If we simply continue to do more of the same we will continue to be victimized. should be reconsidered given our continually advancing capabilities. contact: Anne-marie soederberg. not a military one.ac. AU g U ST 2 0 1 0 | VO l. some of those who are in the best positions to make changes are also under the most pressure to defer change precisely because it requires resources and disruption of the status quo.dk August 25–27 european conference on cognitive ergonomics. email: mereanath @technion. Copyright held by author.purdue. and better separation of privileges could all play a role if used integrally rather than as addons. Police need tools. Additionally.edu August 19–20 International conference on Intercultural collaboration 2010. sIgBed. and the result is an increasing. new delhi.viewpoints There must be a change in the attitude that end users are solely responsible for their systems’ security. safe systems cost-effectively rather as instruments perpetuating legacy decisions. Current and past methods employed against malware have perhaps slowed the growth of the problem but certainly have not stopped it. tX. Bertelsen. will.il evolve into the current worldwide infrastructure.nl August 30–september 3 Acm sIgcomm 2010 conference. Calendar of Events August 16–17 creativity and Innovation in design. copenhagen. integrity monitoring. contact: marilyn claire Wolfe. sponsored: sIgmm. haifa. delft. we should reexamine construction of smaller. not cyberwar. Authors and operators of malware presented with a significant risk of substantial penalties might instead choose to pursue more legitimate professions.dk August 18–20 International symposium on Low power electronics and design. Perhaps. with some creativity. and the problem will get worse. phone: 404-894-5933. Aarhus. phone: 518-782-7875. As a field.gatech. and penetration testing is no substitute for proper design and development. akin to using tax law violations to convict Al Capone. sponsored: sIgchI.au. and a clear mandate to pursue the authors and operators of malware. Eugene h. sponsored: sIgcomm. Change requires resources. contact: olav W. email: bc. This will require a concerted international effort—but the trends are clear that people in every country are at risk if effective actions are not taken. 53 | N O. Austin. contact: neerincx mark. We do not need to do everything everywhere at once—but we do need to start. more protected systems and applications. Spafford (spaf@cerias. denmark. programming languages. email: olavb@cs. and platforms in use should also be reexamined from the perspective of how to build functional. nor should they be forced to buy and maintain a large (and growing) set of additional protections to use their systems safely. Test methods. email: vojin@ece. contact: Vojin g. approaches other than traditional criminal statues might be employed. oklobdzjia. effective techniques such as putting code in read-only devices. email: mark. netherlands.com/rethinking.ucdavis. Unfortunately. Aarhus. Malware and automated attacks have also been evolving. The longer we wait. current and past methods employed against malware have perhaps slowed the growth of the problem but certainly have not stopped it.marktg@cbs. denmark. denmark.dk August 16–20 designing Interactive systems conference 2010. contact: shivkumar Kalyanaraman. sponsored: sIgdA.neerincx@tno. the more difficult (and expensive) it will be to address the problems when we finally attempt to do so. conclusion It has taken decades for computing to g This is a special case of what I described in “Rethinking computing insanity. Technology. email: shivkuma@gmail.ikl@cbs. Known. Most malware is a law enforcement issue. hoping that piecemeal and uncoordinated responses will be enough. and time. phone: 972-482-93260. Customers are not to blame that systems are shipped without appropriate safeguards. gA. authority. Israel. practice and research” available at. code whitelisting. Tools. email: ams. 8 | c om m u n ic aT ion S of T he acm 37 . trained personnel. We are now at a point where it is becoming an existential issue for some companies and even governments.com August 31–september 4 International conference on distributed smart cameras. contact: christensen Bo. everyone should learn that patching a system is not security. Atlanta. email: wolf@ece. It is up to all of us to facilitate the changes that are needed—before too many more anniversaries pass us by. contact: Anath Fischer.g Law.edu september 1–3 symposium on solid and physical modeling. including some that were previously considered to be too complex to be practical. usually unnoticed drag on our innovation and economy. it is cybercrime.edu) is a professor of computer science and the executive director of the Center for education and research in Information assurance and security (CerIas) at Purdue university.
  while remaining ‘just programmed entities’. how should we come to treat these entities? Societal norms and the legal system constrain our interactions with other human beings (our fellow citizens or people of other nations). They will buy goods for us. strives to provide structure to these interactions. or animal entities. bad. In short. does that mean a legally binding contract is formed between their legal principals (the company and me)? A traditional statement of the requirements of a legally valid contract is that “there must be two or more separate and definite parties to the contract. There are. questions must be addressed with respect to artificial agents. or taking them to trial for having committed a crime or something else similarly fanciful. consider Web servers or email daemons for instance. It answers questions such as: What rights do our fellow citizens have? How do we judge them liable for their actions? When do we attribute knowledge to them? What sorts of responsibilities can (or should) be assigned to them? It is becoming increasingly clear these | AU g U ST 201 0 | VO l . along with our current social and economic institutions. while continuing to safeguard our interests? The contracting Problem Discussing rights and responsibilities for programs tends to trigger thoughts of civil rights for robots. and moral philosophy. Consider one problem. 8 . function autonomously and competently. and. other legal persons (corporations and public bodies).e. my shopping bot makes a purchase for me at a Web site).1 they work without human supervision. there must be a consensus ad idem. and in epistemology and metaphysics. But the legal problems created by the increasing use of artificial agents today are many and varied. As we interact with these artificial agents in unsupervised settings with no human mediators. One might think of intelligent agents as a move toward one end of the spectrum of autonomy. t Is A commonplace occurrence today that computer programs.e. which arise from the area of research in artificial intelligence known as intelligent agents. 5 3 | NO. we. taking its cues from these traditions. process our applications for credit cards or visas.V I viewpoints DOI:10. If it is a reasonable assumption that the degree of their autonomy will increase. those parties must be in agreement i.. what place within our legal system should these entities occupy so that we may do justice to the present system of socioeconomic-legal arrangements.. something valuable given in return for the promise.”5 a Jim Cunningham has pointed out that a certain degree of autonomy is present in all programs. the promises of each party must be supported by consideration i.1787248 Samir Chopra Viewpoint Rights for Autonomous Artificial Agents? The growing role of artificial agents necessitates modifying legal frameworks to better address human interests.a And on present trends. political. are capable of doing things that might not be anticipated by their creators or users. will increasingly interact with them. This is the stuff of good. their increasingly sophisticated functionality and behavior create awkward The artificial agent is better understood as the means by which the contract offer is constituted. possibly after carrying out negotiations with other artificial agents. present in ecommerce: If two programs negotiate a deal (that is. learn. The law. and even make decisions on our behalf (in smarter versions of governmental systems such as TIERS2 and in the ever-increasing array of systems supporting legal decision-making3). they are worthy of being termed ‘autonomous artificial agents’. 38 com municaTio nS o f T h e acm questions.4 So. leaving philosophical debates about the true meaning of ‘autonomy’ aside.1145/1787234. those parties must intend to create legal relations in the sense the promises of each side are to be enforceable simply because they are contractual promises. and simplistic science fiction. in parallel. rich philosophical discussions of the normative aspects of these interactions in social.
  Instead. In granting the status of a legal agent to a computer program. Rights and Legal Personhood for artificial agents There are two ways to understand the granting of rights. And when they enjoy such elevation. which their principals might not have agreed to had they been given the opportunity to review the decision. the most important aspect here is that. they are not parties to the contract.viewpoints These requirements give rise to difficulties in accounting for contracts reached through artificial agents and have sparked a lively debate as to how the law should account for contracts that are concluded in this way. while those outside the scope of its authority will not. This entails difficulties in satisfying the requirement the two parties should be in agreement. if the agent’s principal is not aware of the particular contract being concluded. doctrinal difficulties stem from the requirement there be two parties involved in contracting: as artificial agents are not considered legal persons. in relation to the requirement there should be an intention to form legal relations between the parties. since in many cases one party will be unaware of the terms of the particular contract entered into by its artificial agent. In these settings. they 39 IllustratIon by Jo Hn H ersey AU g U ST 2 0 1 0 | VO l. Without this framework. such as legal agency. or when agents capable of determining the terms of contracts are employed. which would require us to grant some legal standing to the programs themselves. only the buyer and seller can be the relevant parties to the contract. Some of its actions will be attributed to its corporate principal (for instance. the terms of use governing individual transactions are not specified. The ‘knowledge’ it acquires during transactions. rather. how can the required intention be attributed? Legal scholarship has suggested a variety of solutions. Viewing a program as a legal agent of the employer could represent an economically efficient. and in a way that safeguards the rights of the principal user and all concerned third parties. The details of this solution aside. to artificial agents. such as customer information. without in any way diminishing our sense of ourselves. Most fundamentally. Furthermore. Therefore. 53 | N O. artificial agents as Legal agents One possible solution. and fair resolution that protects our interests. Given this fact the agent cannot just be understood as a ‘mere tool’ or ‘means of communication’ of the principal. ar Deve t in n pme lo t knowledge of human agents is. doctrinally satisfying. Rights might be granted to artificial agents as a way of protecting the interests of others. and impinge on. Some of the suggested solutions struggle to solve this problem when: protocols between buyers and sellers (and their agents) are not specified in advance. it is an entity with legal standing in our system. the established theory of liability for principal-agent relationships can be applied to this situation. can be attributed to the corporate principal. or perhaps treating them as legal persons like we do corporations or other human beings. though with no well-defined legal standing of their own. the artificial agent is better understood as the means by which the contract offer is constituted. Lastly. We would understand the program as having the authority to enter into contracts with customers. we find ourselves in a situation where increasingly sophisticated entities determine the terms of transactions that affect others and place constraints on their actions. 8 | c om m u n ic aT ion S of T he acm .6 ranging from the idea programs should be treated as “mere tools” of their principals to those suggesting programs be granted full legal personhood in order to grant legal efficacy to the deals entered into by them. agents might arrive at negotiated or reasoned decisions. political. rather. much as human agents do for a corporate principal. the terms of a contract are not finalized via human review. a program is neither a thing nor a tool. and artificial agents might interact with. in a sale brought about by means of an artificial agent. social.7 would be to treat programs as legal agents of their principals. in the way that It will enable us to draw upon a vast body of well-developed law that deals with the agent-principal relationship. Understanding appropriately sophisticated programs as legal agents of their principals could be a crucial step to regulating their presence in our lives. the contracts it enters into). neither third parties nor principals are adequately protected. empowered by law to engage in all those transactions covered by the scope of their authority.b b This discussion is considerably oversimplified but I hope the outlines of the legal problem are clear. we are not so much granting rights to programs as protecting those that employ and interact with them. and legal institutions in such a way that the only coherent understanding of their social role emerges by modifying their status in our legal system—perhaps treating them as legal agents of their principals. unlike a car.
  3 (2001).r.” electronic Commerce research 1. Until then. Wooldridge. the fast-growing literature on agent technologies is truly gigantic. in 19th century England. artificial agents have a long way to go before we can countenance them as philosophical persons. “artificial agents—Personhood in law and philosophy. 204–234. to be published. the Proceedings of the International Conferences on Artificial Intelligence and Law (. Weitzenboeck. A Legal Theory for Autonomous Artificial Agents. springer Verlag. Thus. we did not promote or elevate corporations.f.us/consolidation/Ie/ tIers. I. Samir Chopra (schopra@sci. 183–202.. a. MIt Press. Jennings and M. and the journal Artificial Intelligence and Law are rich sources of information on these systems. women were not full persons. Wooldridge. Harvard Journal of Law and Technology 9 (1996). Ma. in the years to come. “electronic agents and the formation of contracts”. 7. and. and n. see. White. But their roles in our society might grow to a point where the optimal strategy is to grant them some form of limited legal personhood. restatement (second) of Contracts. 2000. (2001). in the modern era. it is worth noting the law has never considered humanity a necessary or sufficient condition for being a person. While the idea of computer programs being legal persons might sound fanciful. 2.” in Proceedings of the European Conference on Artificial Intelligence. International Journal of Law and Information Technology 9. there is a large amount of literature in this area. this area requires an international legal framework to address the ubiquity of artificial agents on the Internet. multidisciplinary debate. 8 References and Further Reading 1.” Gunther Teubner notes that animals were often treated as legal actors including being brought to trial.org/ past-icail-conferences/index. 4. and their deployment across national borders. 40 com municaTio nS o f T h e ac m | AU g U ST 201 0 | VO l .. the corporation has been granted legal personhood. we can only expect that more complexities and subtleties will arise. for introductions.lea-online. d The work being done on the “Alfabiite” project (at Imperial College London. NRCCL Oslo. 25–52.. the real question is whether the scope and extent of artificial agent interactions have reached such a stage. Agent Technology: Foundations. An entity is a viable candidate for legal personality in this sense provided it fits within our networks of social. allan and r. “Can computers make contracts?”. Artificial agents have a long way to go before we can countenance them as philosophical persons. university of Michigan Press.net/pubs 5. and economic relations in such a way that it can coherently be a subject of legal rulings. Reasoning about Rational Agents.shtml 3. § 3 6.iaail.” emory law Journal 50. Cambridge. Chopra and l. .edu) is an associate professor in the department of Philosophy at brooklyn College of the City university of new york.html). see M. 1998. Kerr. In so doing. For example. s. eds. Various international trade agreements such as those formulated by the unCItral or national legislations such as the uCIta have not as yet resulted in clarity in these areas.. Copyright held by author. The question of legal personality suggests the candidate entity’s presence in our networks of legal and social meanings has attained a level of significance that demands reclassification. we should acknowledge their growing roles in our lives and make appropriate adjustments to our legal frameworks so that our interests are best addressed.J. political. “ensuring the success of contract formation in agent-mediated electronic commerce. Chopra and l.brooklyn. complex. 1063. e.viewpoints we attended to the interests of humans.hhs.cuny. c In his Max Weber Lecture. c. Indeed. “Contracting with electronic agents. 4 (2001).tx. must conform to the standards expected of the other entities that enjoy standing in our legal system.c The decision to grant personhood to corporations is instructive because it shows that granting personhood is a pragmatic decision taken in order to best facilitate human commerce and interests. White. 2004 and s.state. a very good source of material on the legal issues generated by the increasing use of artificial agents may be found at the law and electronic agents Workshops site:. Halsbury’s Laws of England (4th edition) Vol. CIRFID Bologna) may be of interest in providing guidance in this regard. “Rights of Non-humans? Electronic Agents and Animals as New Actors in Politics and Law. 5 3 | NO.d I have merely scratched the surface of a huge. 9 paragraph 203.J. Applications and Markets. bellia Jr. Widdison. some very good treatments of the contracting problem may be found in: t.
  TX. since traditional historical sources are frequently incomplete. Dijkstra is well known for his contributions to computer science as well as his colorful assessments of the field. 53 | N O.V T viewpoints DOI:10. Transcripts from these oral histories are a key source in understanding the history of computing.” Winner of ACM’s A. His contributions to this magazine continue to enrich new generations of computing scientists and practitioners. reflects on a programmer’s life. edu/oh. this interview has been condensed from the complete transcript. he chARLes BABBAge InstItute holds one of the world’s largest collections of research-grade oral history interviews relating to the history of computers. 8 | c om m u n ic aT ion S of T he acm PHotoGra PH Court esy oF t H e unIVersIt y oF texas at au st In 41 .1787249 Thomas J. Turing Award in 1972. in August 2001 for a NSF-KDI project on “Building a Future for Software History. which facilitate the interviewer’s extensive preparation and often suggest specific lines of questions. —Thomas J. Misa AU g U ST 2 0 1 0 | VO l. and networking. Misa.umn. available at. software. in one of his last interviews before his death in 2002. Most of the 350 interviews have been conducted in the context of specific research projects. Editor Interview An Interview with edsger W.1145/1787234. We present this interview posthumously on the eighth anniversary of Dijkstra’s death at age 72 in August 2002. This interview with programming pioneer Edsger Dijkstra (1930–2002) was conducted by CBI researcher Phil Frana at Dijkstra’s home in Austin.cbi.M. dijkstra The computer science luminary.
  they were working on the ARRA. And it gave me the dear opportunity for a one-upmanship that I never got again. whom I had never met before. but for the more reliable ARMAC I could try something more ambitious. I could honestly say. I got my degree and we had the festive opening of the ARMAC. and tired. pentodes. In those years I was a very conservative programmer. and I then c Automatische Rekenmachine MAthematische Centrum = Automatic Calculator Mathematical Centre | AU gU ST 201 0 | VO l . we sat down on the café terrace to drink a cup of coffee and I was just thinking about whether I could do this. “Dr. I was supposed to study theoretical physics. I also began to realize that in some strange way. I think that “programmer” became recognized in the early 1960s. For a demonstration for noncomputing people you have to have a problem statement that non-mathematicians can understand. The installation I did together with the young Gerrit Blaauw who later became one of the designers of the IBM 360. However. who was the director of the Computation Department of the Mathematical Centre in Amsterdam. I mean a zero is a zero and a one is a one. trying to follow a course on a totally new topic. And it was that unforgivingness that challenged me. they were trying to build them. England. and the mathematicians were dismissive and somewhat contemptuous about computing. and other electronic gear. One funny story about the Fairchild F27: On my first visit to Australia. And we arrived and I met my host. if something went wrong. And he was very apologetic that this world traveler had to do the last leg of the journey on such a shaky two-engine turboprop. So the FERTA. I became the programmer of the Mathematical Centre in March of 1952.viewpoints how did your career start? It all started in 1951. and he agreed that there was no such thing as a clear scientific component in computer programming. the form of the instruction code on paper. it was just a mixture of being ingenious and being accurate. when my father enabled me to go to a programming course in Cambridge.a but they could not get it reliable. And there was nothing I could point to! I spoke with van Wijngaarden in 1955. I concluded that the intellectual challenge of programming was greater than the intellectual challenge of theoretical physics. It was a frightening experience: the first time that I left the Netherlands. you could not enter the term “programmer” into your marriage record? That’s true. I was trained to become a scientist. The Netherlands was such a small country that Aad van Wijngaarden. If something went wrong. as soon as I had decided to become a programmer. had been so unreliable that the only safe demonstration we dared to give was the generation of random numbers. The way in which programs were written down. a few years earlier. I had never used someone else’s software. Now the ARRA. it was very much modeled after what I had seen in 1951 in Cambridge. to become a programmer instead. b Fokker Electronische Rekenmachine Te Amsterdam = Fokker Electronic Calculator In Amsterdam Sydney or Melbourne. and as a result I chose programming. The first eight years of my programming there I developed the basic software for a series of machines being built at the Mathematical Centre. since I no longer felt welcome at the university: the physicists considered me as a deserter. friends. the library organization. Stanton. At the time programming didn’t look like doing science. then on another 747 I flew to a Automatische Relais Rekenmachine Amsterdam = Automatic Relay Calculator Amsterdam. The final part of the journey was on an F27 to Canberra. the first time I ever had to understand people speaking English. I was all by myself. knew of this. But I liked it very much. using selenium diodes. In 1956 I did two important things. And on a part-time basis. What’s the shortest way to travel from Rotterdam to Groningen? It is the algorithm for the shortest path. And at the time. 5 3 | NO. When you got married in 1957. I envied my hardware 42 comm unicaTio nS o f Th e ac m i had never used someone else’s software. And then the Mathematical Centre built a machine for Fokker Aircraft Industry. but that I might very well be one of the people called to make it a science. on which I had selected 64 cities (so that in the coding six bits would suffice to identify a city). and it was that unforgivingness that challenged me. using a somewhat reduced roadmap of the Netherlands. and he offered me a job. I had done it. while I was still a student. So I designed a program that would find the shortest route between two cities in the Netherlands. In the mathematical culture of those days you had to deal with infinity to make your topic scientifically respectable. 8 . As I said. was built and installed at Schiphol. Programming was so unforgiving. programs could become very complicated or tricky. with Gene Amdahl and Fred Brooks. If something went wrong. i had done it. I felt quite safe: I calculated the resonance frequencies of the wings myself. So it was in 1955 when I decided not to become a physicist. in 1955 after three years of programming. because if you asked them what their professional competence consisted of. which I designed in about 20 minutes. there’s a curious story behind your “shortest path” algorithm. and an updated version was built.” [laughter] In 1956.b an updated version of the ARRA. What projects did you work on in Amsterdam? When I came in 1952. I flew on a big 747 from Amsterdam to Los Angeles. One morning I was shopping in Amsterdam with my young fiancée. they could point out that they knew everything about triodes. I finished my studies as quickly as possible. I was the kind of guy to whom you could say such things. they even have to understand the answer. and that was the reason for going to Cambridge.c We had to have a demonstration. They didn’t have computers yet.
  Bauer. The publication is still quite nice. but surely you must be up to it…” I learned to cope with it. but at the expense of much more hardware than we could afford. to my great amazement. And then our ways parted. Without pencil and paper you are almost forced to avoid all avoidable complexities. the os/360 monitor idea would have never occurred to a european? No. the American reaction was very different. 53 | N O. 8 | c om m u n ic aT ion S of T he acm in the mathematical culture of those days you had to deal with infinity to make your topic scientifically respectable. you want to go from here to there and you have a car with a GPS and a screen. We did not allow ‘After-you-after-you’ blocking. where the programs would compete for access to the critical section and the dilemma would never be solved. these days. because a real-time interrupt occurs at an unpredictable moment. thesis. What are the things I have to show? How can I prove them? Having d This is an implementation of the mutual exclusion problem. at the time. And it jumped again recently because it is extensively used in all travel planners. it could replay it again. In the meantime I had also designed the shortest sub-spanning tree for my hardware friends. There was not a way to test them. it can give you the shortest way. How do you minimize the amount of copper wire that connects these points? So I wrote “A note on two problems in connection with graphs. and about the relative speeds of the programs nothing is known. from now onward I only accept a solution with an argument why it is correct. I would write down the formal specification of the machine. I found it in the early 1960s in a German book on management science—“Das Dijkstra’sche Verfahren” [“Dijkstra’s procedure”]. I wrote a real-time interrupt handler that was flawless and that became the topic of my Ph. When was the “shortest path” algorithm originally published? It was originally published in 1959 in Numerische Mathematik edited by F. The construction and counterexamples became even more time-consuming. He had analyzed what kind of proof would be needed. This was a major difference between European and American attitudes about programming.D.10 how could you tell if early programs were correct? For those first five years I had always been programming for non-existing machines. If. Dekker came with a perfect solution and a proof of its correctness. how did the notion of program proofs arise? In 1959.3 Later I would learn that this would almost be considered an un-American activity. Now. One of the reasons that it is so nice was that I designed it without pencil and paper. We would design the instruction code. Consider two cyclic programs. but they were all wrong. When IBM had to develop the software for the 360. and in each cycle a section occurs called the critical section. the idea of a real-time interrupt created a vision of a program with non-reproducible errors. A simple writing error did not matter as long as the machine wasn’t there yet. so to speak. Try to synchronize these programs in such a way that at any moment in time at most one of them is engaged in its critical section. sorry. You know. Needless to say. and as soon as errors would show up on the machine.” Within three hours or so Th. three years later. we were too poor to consider it and we also decided that we should try to structure our designs in such a way that we could keep things under our intellectual control.d I looked at it and realized it was not trivial at all. All the programming I did was on paper. yes. For instance. Eventually that algorithm became. Suddenly. so you’ve got to convince yourself of their correctness by reasoning about them.L. they never got the OS/360 right. So they made it reproducible. and all three of us would sign it with our blood. the other one should go on unhampered. they would be simple to correct. how was the computing culture in America different? Well. For each. if one of the programs would stay for a very long time in its noncritical section. But in 1957. The two programs can communicate by single reads and single writes. 43 . “Have you designed the algorithm for GPS?” It turned out he had seen the Scientific American of November 2000. which later became a cornerstone of the THE multiprogramming system [THE = Technische Hogeschool Eindhoven (Technical University Eindhoven)]. there was a method named after me.viewpoints designed the algorithm for the shortest path. “Yes. it was a 20-minute invention. Now. As I said. AU g U ST 2 0 1 0 | VO l. one of the cornerstones of my fame. I said. That is an extra piece of machinery that would exactly record when interrupts took place. on the big panel you have to connect a whole lot of points with the same copper wire because they have to have the same voltage. and I had to change the rules of the game. J. I would check whether I could live with it. there were all sorts of side conditions. I had challenged my colleagues at the Mathematical Centre with the following programming task. they built one or two machines especially equipped with a monitor. yes.”2 Years later when I went to my ophthalmologist—he did not even know that I was a computing scientist—he said. And if something went wrong. I would sketch a scenario that would reveal the bug. my friends at the Mathematical Centre handed in their solutions. People made their programs more sophisticated and more complicated. it was published in 1959. we see your problem. and my hardware friends would check that they could build it. My hardware friends said. In fact. So I was quite used to developing programs without testing them. an algorithm for the shortest path was hardly considered mathematics: there was a finite number of ways of going from A to B and obviously there is a shortest one. so what’s all the fuss about? It remained unpublished until Bauer asked whether we could contribute something. “Sir.
  So i was quite used to developing programs without testing them. That made a tremendous difference! It turned pars44 comm unicaTio nS o f Th e acm ing into a rigorous discipline. It also introduced about a half-dozen profound novelties. The draft ALGOL 60 report was circulated in one of the last weeks of December 1959. FORTRAN was essentially defined by its implementation. with the meetings for the design of ALGOL 60. It turns the Boolean expression from a statement of fact that may be wrong or right into an expression that has a value. It was something like “Any other occurrence of the procedure identifier denotes reactivation of the procedure. First of all. had to replace him. etc. no longer a lot of handwaving. I was once asked what were the most vital assets of a competent programmer.” The fourth novelty was the introduction of recursion into imperative programming. Recursion was a major step. but she could not make that step. the power of IBM. The concept was quite well known. with recursion emphatically ruled out. 8 . When did you understand that programming was a deep subject? I had published a paper called “Recursive Programming. 5 3 | NO. a formal definition was given. while I did the programming work. That’s how recursion was explicitly included. There is an enormous difference between one who is monolingual and someone who at least knows a second language well. It was tough. and I think that is a tragedy. the definition should define what the implementation should look like. though it wasn’t stated. It was introduced in a sneaky way. It was a group that together would implement a subset of ALGOL 60. Another experience in 1959 was attending the “zeroth” IFIP Congress in Paris. It played a major role in making computing science academically respectable.” again in Numerische Mathematik. You lose a lot when you restrict the role of mathematics to program verification as opposed to program construction or derivation. Finally. it introduced the absence of such arbitrary constraints as. stores. | AU gU ST 201 0 | VO l . Was this called recursion at that time? Oh yes. Bauer would never have admitted it in the final version of the ALGOL 60 Report. Oh yes. And I said “exceptional mastery” of his native tongue because you have to think in terms of words and sentences using a language you are familiar with. I said “mathematical inclination” because at the time it was not clear how mathematics could contribute to a programming challenge. Aad van Wijingaarden. I’ll never forget the excitement!—and dictated to him one suggestion. “three plus five is ten” was not a complicated way of saying “false”. He immediately founded the ALCOR Group. She was a gifted mathematician. My international contacts had started in December 1958. the definition of the semantics was much less operational than it was for existing programming languages. But perhaps more important. What were other novelties in ALgoL 60? A fifth novelty that should be mentioned was the block structure. Now these are five or six issues that for many years the United States has missed. ruling out the subscripted subscript. and Jaap Zonneveld and I. and I have never been able to figure out who was responsible for that synthesis. And F.L. Zonneveld was a numerical analyst. “true” or “false. say. And of all the people who had to agree with the report. it’s useful. We studied it and realized that recursive calls were all but admitted. We made it overlookable. it made compiler writing and language definition topics worthy of academic attention. whereas with ALGOL 60 the idea emerged that the programming language should be defined independent of computers. Now the reason that ALGOL 60 was such a miracle was that it was not a university project but a project created by an international committee. it was just wrong. I was beginning to realize that programming really was an intellectual challenge. the general feeling at the time that programming was something that should be doable by uneducated morons picked from the street. You will discover that certain constructions in one language you just can’t translate. had had a serious car accident. The third novelty was the introduction of the type “Boolean” as a first-class citizen.” How great that step was I learned from my mother’s reaction.8 In 1961. none saw that sentence.. Yes… false dreams paralyzed a lot of American computing science.viewpoints settled that. you’ve remarked that learning many different languages is useful to programming. For her. had he known it. how was ALgoL 60 a turning point? Computing science started with ALGOL 60. because mathematical proofs. say. with the same use of the word “structure” as I used nine years later in the term “structured programming. can now be rendered as simple calculations that reduce a Boolean expression by value-preserving transformations to the value “true. The ALGOL 60 meetings were about the first time that I had to carry out discussions spontaneously in English. because it makes you much more conscious about language structure in general.” That sentence was inserted sneakily. compilers. A second novelty was that at least for the context-free syntax. all the programming i did was on paper.” The concept of lexical scope was beautifully blended with nested lifetimes during execution. It was included in LISP. it should not require any sophistication. My boss. It was a tool for structuring the program. It was the obsession with speed. which was beginning to emerge at that time. as his immediate underlings. he wrote down a program that met the proof’s requirement. but I was deeply impressed when I saw it. And I phoned Peter Naur—that call to Copenhagen was my first international telephone call. Potentially this is going to have a very profound influence on how mathematics is done. the example I mentioned.
  How did I characterize it? “APL is a mistake. I wrote “Cooperating Sequential Processes. In my Turing Lecture I described the week that I studied the specifications of the 360.11 I characterized the Russian decision to build a bit-compatible copy of the IBM 360 as the greatest American victory in the Cold War. 1964–1965. that was totally new for me. completes the proof. but that was clearly not a part of the IBM culture. It was very algebraic and complicated. which Tony Hoare later named the Problem of the Dining Philosophers. And I visited a number of Burroughs offices.”1 1968 was also the year of the IBM advertisement in Datamation. England. and gave an invited speech on advancing programming. Okay now. And I couldn’t understand those questions either. The other thing I remember was a conference in Rome on symbol manipulation. In the audience was Tony Hoare. the fence around a university campus. and van Wijngaarden. the first lecture at that ACM workshop was given by a guy from IBM. my thinking about program synchronization resulted in the P.” Well. the author believes. During a reception. is here [in the U. Scholten the hardware channels and the interrupts of the Electrologica X8. carried 45 Thanks to my isolation.s. in Munich.7 He should have known about the care that has to go into the design of such things. that was the first time I met Donald Knuth. The editor who made this change was Niklaus Wirth. Why is “elegance” in programming important? 1968 was exciting because of the first NATO Conference on Software Engineering.” and I invented the Problem of the Dining Quintuple. It was at that meeting where one afternoon I explained to Brian Randell and a few others why the GO TO statement introduced complexity. That was to an ACM Conference in Princeton. In 1962.” with X anything. I think. because there were serious flaws built into the I/O organization of that machine. I got a number of curtain calls: clearly I was saying something unusual. i would do things differently than people subjected to the standard pressures of conformity. And they paid me $500. This had gone on for an hour or so. of a beaming Susie Meyer who had just solved all her programming problems by switching to PL/I. I don’t remember him because he was one of the many people in the audience. But there were many people that joined the discussion and posed questions. i was a free man. So I sent an article called “A Case Against the GO TO Statement” to Communications of the ACM. Of course. because there was an ACM workshop with about 60 to 80 participants and I was invited to join. “GO TO Statement Considered Harmful.” [laughter] This may be included in an oral history? It’s not mathematics. And in doing so. was in 1963. he changed the title into. so we had to give the first slot to an IBM speaker. and for two years I lectured on numerical analysis. the last machine my friends built. Quite an amazing experience. both bearded and both with a Continental accent. was [laughter] the darkest week in my professional life. I voiced my worry that I was there on false premises. on “A Constructive Approach to the Problem of Program Correctness.”4 That title became a template. but neither of us remembers that. I was extremely cross with Gerry Blaauw. it On the blackboard he wrote wall-towall formulae and I didn’t understand a single word of it. I did not understand a word of it. By 1963–1964. I went to the first IFIP Congress.” he said. with his wife. they just would like me to be there.” “Oh. in Garmisch. how did go to become ‘harmful’? In 1967 was the ACM Conference on Operating Systems Principles in Gatlinburg. AU g U ST 2 0 1 0 | VO l.] not as high as I was used to. I didn’t need to sit in a panel discussion. Hundreds of writers have “X considered harmful. That was all nonsense and gibberish. I must already have had some fame in 1963. so he turned it from an article into a Letter to the Editor. but we made it the rule that we would go to the microphone in turn. have merged into one person. 1964 was the year in which IBM announced the 360. “The first speaker. Those were the days we were led to believe that the problems of programming were the problems of the deficiencies of the programming language you were working with. In a NATO Conference on Software Engineering in 1969 in Rome. was sitting next to an American and at a given moment the American grabs his shoulder and says “My God! There are two of them. There were panel discussions and Peter and I were sitting next to each other and we had all sorts of nasty comments. “none of us did. I didn’t need to give a speech. it isn’t computer science either. my boss. In BIT I published a paper.& Voperations.5 When did you first visit the u. but it is a true story…. What about your first two trips to America surprised you about the profession? Well. Let’s say that the fence between science and industry.S. And they asked me to publish it.S. In September 1962. Peter Naur was there. in April or so. was the first time that I had a large American audience. and he doesn’t remember it because in his memory Peter Naur and I. and then I started on the design of THE multiprogramming system. Then I became a professor of Mathematics in Eindhoven. The editor of the section wanted to publish it as quickly as possible. [laughter] We reconstructed years later that we were both there.viewpoints Peter Naur and I were main speakers at a workshop or a summer school in Brighton. there were quite a number of well-known British scientists in that audience. 8 | c om m u n ic aT ion S of T he acm . but IBM is sponsoring this. I had designed with Carel S. 53 | N O.? My first trip to the U. “And this. That.” According to Doug Ross. I had generalized Dekker’s solution for N processes and the last sentence of that one-page article is. it was the first publication of an algorithm that included its correctness proof.
  combined with the benefits of participating in live classroom discussion and interaction. I had just become a professional programmer.25 X 4. In the oral examination we solved a problem. I think he outgrew it before his death. The European mind tends to maintain a greater distinction between man and machine. the kid got stuck.viewpoints through to perfection. it was not considered an interesting market. I was beginning to see American publications in the first issue of Communications of the ACM. And having been educated in FORTRAN. And APL. There | AU gU ST 201 0 | VO l . Only recently I learned that in constant dollars the development of the IBM 360 has been more expensive than the Manhattan Project. M. I was shocked by the clumsy.75 that it had been written at the other RSS COMMUNICATIONS OF THE ACM queue. We would be much better served by clean. I wrote “Notes on StrucCase Studies tured Programming. we overrate its importance. the “electronic brain” or “machines that think... at a time when I had published very little. Freud never became the rage in Europe as he became in the United States. although it was a construction that he had seen me using at my lectures. The use of anthropomorphic terminology forces you linguistically to adopt an operational view.”6 which I think JOB 9-513 Multimedia owed its American impact to the fact 2.org a graduate computer science program that offers you the convenience and access of online learning. decided what had to be done.] for the better part of 17 years. There is also a great cultural barrier. but very close to the end. immature way in which they talked about computing. side of the Atlantic Ocean. We were spared the pressure. at a given moment your pattern of understanding becomes visualizing what happens during the execution of the algorithm. look at what that 1963 invitation to the ACM workshop illustrates. he couldn’t think of it.m.? One of the things that saved Europe was that until 1960 or so. It turned out he had to write a subscripted value in a subscript position. 10:30 a. with its one-liners.” That is absolutely killing. “the tools we use have a profound and devious influence on our thinking habits. IMAGINE. Saturday. the idea of a subscripted subscript.acm. it is always due to the fact that they had learned programming in a programming language that did not permit it. If you are now trained in such an operational way of thinking. 6:00 p.” The devious influence was inspired by the experience with a bright student.S. I was a free man. It’s less inclined to describe machines in anthropomorphic terminology. 8 . And it makes it practically impossible to argue about programs independently of their being executed. something that was not allowed in FORTRAN.s.edu greater access to excellent education 46 communicaT io nS o f T h e acm What were other differences between europe and the u. Content Written by Experts Blogs Articles Why did your “structured programRoundtables ming” have such impact? In 1969. It’s here. So we were ignored. with a sense of elegance. which has two very different sides. Together we constructed the program. went in the other direction. When young students have difficulty in understanding recursion.” was a very heavy use of anthropomorphic terminology. I had implemented ALGOL 60 and I had written a real-time interrupt handler.S. August 21. It is the language of the future for the programming techniques of the past: it creates a new generation of coding bums. it’s also less inclined to describe the human mind in mechanical terminology. you’ve said. I have been exposed to more APL than I’d like because Alan Perlis had an APL period.” I thought that programmers should not be puzzle-minded. I would do things differently than people subjected to the standard pressures of conformity. we underrate the importance of isolation. Yet I turned out to be quite well known. so the use of FoRtRAn made him unable to solve that? Indeed. 5 3 | NO. having lived here [in the U.. August 18. Is this why artificial intelligence research seemingly doesn’t take hold in europe? There was a very clear financial constraint: at the time we had to use the machines we could build with the available stuff. How come? Thanks to my isolation. I can talk about this with some authority.m. in Computer Science Brooklyn Campus Information Session Wednesday. significantly reducing the amount of time you’ll spend on campus and maximizing interaction with faculty members and fellow students. and therefore on our thinking abilities. 718-488-1011 • gradadmissions@liu. See. but for many years APL was “it. systematic minds.. I had no idea of the power of large companies. I think that thanks to the greatly improved possibility of communication. I was amazed because he had understood the problem perfectly. Even stronger. the Brooklyn Campus of Long Island University is offering a NEW BLENDED LEARNING program that fuses online learning with traditional classroom studies. which was one of the criteria on which IBM selected programmers.
  1969). eds. dahl. Penguin books ltd. b.—but not in europe? A major reason is timing. we used to cooperate on large projects and apply a division of labor. Go to statement considered harmful. it pays so much to have a well-trained mathematical mind. you can still observe it is the Department of Computer Sciences. e. In o. 2. dijkstra. 1–82. 3 (1968).D. e. Today the English prefer Information Technology. e. dijkstra. 3 (Mar. and C. such as the Association for Computing Machinery. 312–318. Communication with an automatic computer. dijkstra. and deadlock prevention. when we started to design a computing science curriculum in the 1960s. slightly different meanings. Numerische Mathematik 1 (1959). as Morris Kline illustrates eloquently.d. Europe. It’s lovely. 269–271. and buxton. somewhere in the small print.s.W.a. 11. departments of computer science were founded before the shape of the intellectual discipline stood out clearly. Quite regularly I see firm XYZ proposing to give student fellowships or something and then. Is there a relationship between the curriculum and the nature of funding of universities? Yes. 147–148. departments of computer science were founded before the shape of the intellectual discipline stood out clearly. dijkstra. Tony Hoare was a Professor of Computation. but that time there were at least as many computer sciences as there were professors. BIT 8. 115–138. and at the time it ruled out all FORTRAN courses.viewpoints The only way in which you can see the algorithm is as a FORTRAN program. a note on two problems in connection with graphs. the financing of the university. In many places. that preference will be given to students who are supervised by professors who already have professional contact with the company. M. nato. refused to do so. 8 | c om m u n ic aT ion S of T he acm 47 . Is the outcome of the curricula different in europe and America? I must be very careful with answering this because during my absence. circulated privately. 20–22.W. Harmondsmorth. They made so much protest that Cor Ligtmans.cs. sharing. I was disappointed in America by the way in which it rejected ALGOL 60. over de IbM 360. IT. recursive programming.W. Numerische Mathematik 2 (1960). Europe was later. Hierarchical ordering of sequential processes. So the American computing industry emerged earlier. it was something of a shock when I went to the Department of Mathematics at Eindhoven where everybody worked all by himself. e. it coined the term Informatics. 174–186. Why do computer science departments often come out of electrical engineering in the u. Commun.. e. 10. oct. Menduno. But a major difference was that the fence around the university campus was higher.d. The computing industry asked for graduates. and the fraction pressure on the universities to supply them. dijkstra.W.. J. “Information” came a bit later on? It was the French that pushed informatique. Ph. 1972. Scientific American 283. who should have written his Ph. References 1. was later. Yes. And they still suffer from it. Software Engineering Techniques: A Report on a Conference Sponsored by the NATO Science Committee (rome. london. and Information Systems. e. the role of the university. And what’s the answer then for our future students to avoid the same trap? Teach them. 3. Rather than the department of computing science or the department of computation. You notice that all important words carry different. without knowing Dutch. After we had completed the THE System. even if the university did not quite know how. Mathematics in Western Culture. M. dijkstra. If you start to think about it. university of amsterdam. in Communications of the ACM. I consider it a tragedy because it is a symptom of how the United States is becoming more and more a-mathematical. e. That already started in the 1970s. 11 (nov. a constructive approach to the problem of program correctness. one of the firm rules was that no industrial product would be the subject of an academic course. wrote that european programmers are fiercely independent loners whereas Americans are team players. ACM 11.W.. Nico Habermann wrote a thesis about the Banker’s Algorithm. During 1968 in Garmisch I learned that in the ears of the Americans. Structured Programming.W. We taught ALGOL 60. 9. as soon as possible. randell. england. it was a much greater eye-opener than FORTRAN.9 Precisely in the century which witnesses the emergence of computing equipment.n. dijkstra. you can hear the word “machine” in that name. dijkstra. 4. 7. Kline. IS. notes on structured programming. a decent programming language that exercises their power of abstraction. you can only laugh. or is it the other way? At the Mathematical Centre. So whatever I say about the [European] university is probably idealized by memory. Acta Informatica 1 (1971). eds. academic Press. e. 6. I had not expected it.edu/ users/ eWd/ewd02xx/eWd255.. 5.utexas. It has the greatest influence on the funding of research projects. Italy.W. e. in many places.r. why you can’t (always) get there from here. 1970. damaged by World War II. 2000). dissertation. n. a “mathematical engineer” [such as we educated in Eindhoven] was a contradiction in terms: the American mathematician is an impractical academic. for instance. eWd 255.. at the University of Texas. It’s the British Computer Society and it was the Dutch who had Het Nederlands Rekenmachine Genootschap. For financial reasons. of the population it is supposed to address have changed radically. Hoare. Middlesex. 1968). 1959. I think the timing has forced the American departments to start too early. atlas shrugged: When it comes to online road maps. The department did not like that because it was not clear how much he had done by himself. Here.. whereas the American engineer is practical but hardly academically trained.W. dijkstra.-J. You also find it reflected in the names of scientific societies. This immediately rules out all Java courses. 53 | N O.W. Copyright held by author.PdF 8. And you got the departments of Computer Science. 1972. To give you an example. thesis on another aspect of THE System. which increased the AU g U ST 2 0 1 0 | VO l. In 1963 peter patton. and about scheduling.
  It’s Joe. communicaT io nS o f T h e acm | AU gU ST 201 0 | VO l . in formality. Jane uses her development environment to search for all the places where her product uses the unsupported library. she brings up relevant code in her development environment to relate the diagram back to the code.1787250 Article development led by queue.org Could ubiquitous hand-drawn code map diagrams become a thing of the past? By RoBeRT DeLine. but representative story: Jane is a developer who has been a member of her team so long that everyone calls her the team historian.1145/ 1787234. Although the practice illustrated in the story is widespread and useful. to anchoring a conversation. from solo use. As she talks Joe through a use case. she overlays the diagram with arrows to show how different parts of the system interact. Joe feels confident he understands the design and heads back to his office. to communicating with the whole team or user community. As she jumps around the code base. From time to time. 5 3 | NO. Jane’s development environment now has dozens of open documents. 48 PHotoGra PH deta Il oF F IG ure 1 . They start the conversation by looking at an architectural diagram tacked to the wall near Jane’s computer. the newest member of the team. sketching only the relevant parts of the architecture but in more detail than the printed diagram. from the duration of a single task to an entire release cycle. the diagrams are typically not tied to the code.acm. and in audience. anD kaeL RoWan Software Development with code maps soFtWARe deVeLopeRs ReguLARLy draw diagrams of their systems. To go from architecture-level to code-level discussions requires switching tools—for example. Jane goes back to her own work. To get a sense of how diagramming fits into a developer’s daily work. in longevity. Jane is finally getting around to some code cleanup she had planned for ages—namely. This story illustrates the wide range of diagramming practice.practice Doi:10. As the team historian. dropping a dependency on a library that is no longer supported. The diagrams range in quality from sketches to high-quality posters. . there are a few downsides where software could make an improvement. and carries on exploring the dependency on the unsupported library. finds her place in the search results. she sketches a class diagram on a notepad to capture the architectural dependencies she discovers. Gina VenoLia. Jane draws a version of the diagram on the whiteboard. Since the product just shipped a few weeks ago. After several minutes. She clicks through the results one by one and reads the code to understand how it uses the library. there’s a knock at the door. Jane tries to resume her task but cannot find where she left off in all the clutter. from idiosyncratic scribbles to welldefined notations. reissues her original search. consider this fictitious. She closes all open documents. Between exploring the search results and answering Joe’s questions. 8 Partway through this code-understanding task. To get into specifics. First. Jane is accustomed to this type of question. He is working on a bug and is confused about how one of the product’s features is implemented.
  53 | N O.ar Deve t in n pme lo t Cred It t K AU g U ST 2 0 1 0 | VO l. 8 | c om m u n ic aT ion S of T he acm 49 .
  Second. What is the program supposed to do? 3. These navigation steps are not just for editing the code. from the whiteboard to the development environment. she follows hyperlinks. What code caused this program state? 2. Jane’s code search and notepad diagram are not tied together in any way. information needs that are related to diagramming behavior. 8 . such as jumping from a method caller to a callee. such as zoomable box-and-line diagrams9 and cityscapes. The software visualization community has previously explored different types of maps. With so much discontinuous navigation. For example. The two can easily get out of sync and cannot be stored or retrieved together. What are the implications of this change? no visual transition to show where the jump landed. For example. The code consists of many thousands of symbols.or conversation-specific diagrams. and could serve as a “map” to help keep developers oriented. Third. there is no transition between team-level documentation and task. As a developer navigates the code. Getting lost in a large code base is altogether too easy. there is a lost opportunity to help deal with the disorientation Jane feels when confronting all the open documents on resuming her task. Why was this code implemented this way? 4. 1. four diagrams of the oahu system. What is the purpose of this code? 2.10 for tasks such as program understanding and analyzing 50 communicaT io nS o f T h e acm | AU gU ST 201 0 | VO l . as when Jane’s diagram was available during task resumption but her search results were gone. Software developers also have a frequent need for information during their programming tasks. What is statically related to this code? 3. a developer can easily become disoriented. Better support for code diagrams in the development environment could support code understanding and communication.practice figure 1.8 To try to find answers. they browse around the code and other documents.7. 5 3 | NO. which adds both relevant and irrelevant documents to the environment’s working set. This separation also causes poor task support. What code could have caused this behavior? 1. with Table 1. Jane has to reproduce parts of the poster on the whiteboard in order to answer Joe’s specific questions. with few visual landmarks to guide the eye. The more she navigates. the greater the pileup of document tabs.
  and we collected many example diagrams along the way. While typically done solo. ad hoc communication with coworkers was a common way of addressing a variety of information needs. To address these issues. manually recorded their activity minute by minute. ˲˲ Ad hoc meetings. 53 | N O. Is this problem worth fixing? 4. This suggests the plausible utility of a code map that answers these needs either directly or through interaction. 8 | c om m u n ic aT ion S of T he acm 51 . specific information needs when trying to understand existing code and planning code changes. Most ad hoc meetings were small. and then surveyed more than 400 developers to understand the scenarios more deeply. Our goal is to integrate maps into the development environment such that developers can carry out most tasks within the map. and they often use diagrams when looking for answers. From these two studies we know that developers have frequent. vet a decision. fix a bug. and could serve as a “map” to help keep developers oriented. Consistent with the previous study. or make the program structure better match its functionality. involving two or at most five people.3 The three most frequently mentioned scenarios were: ˲˲ Understanding existing code. a Microsoft Visual Studio plug-in that replaces the tabbed documents with a zoomable code map. using a user-centered approach we are designing an interactive code map for development environments. we interviewed nine developers at Microsoft to identify common scenarios. Better support for code diagrams in the development environment could support code understanding and communication. In preparation for our initial design we conducted a series of field studies at Microsoft Corporation. How have resources I depend on changed? 7. Top information needs for which software developers turned to their coworkers. What is the program supposed to do? 5. What are the implications of this change? 3. Examining source code and its behavior to develop an understanding of it. In our observations. and coded these logs into 334 instances of information-seeking behavior. or help work through a problem. we identified 21 general information needs. More than half of survey respondents indicated that diagrams were important in these scenarios. We interviewed developers to find how and why they draw diagrams of their code.7 We observed 17 developers at Microsoft for approximately 90 minutes each. Table 2 shows the information needs that were most frequently addressed by talking with coworkers. clustered into seven work categories. In what situations does this failure occur? 6. understanding existing code and designing/refactoring often involved pairs or small groups. We also know that developers often turn to coworkers to find the answers they need. This reliance on conversations with coworkers corresponds with the ad hoc meeting scenario from the diagramming study.practice project data. we found many of their information needs fell into the categories of understanding execution behavior and reasoning about design. ˲˲ Designing/refactoring. In a separate study we sought to understand developers’ information needs while carrying out their development tasks. What have my coworkers been doing? 2. and they create diagrams to Table 2. Asking a coworker to explain existing code.1 Using insights from these three studies.3 We also directly observed developers at work to watch their information-seeking behavior and to catalog their information needs. These maps are typically designed to supplement a standard development environment. What code could have caused this behavior? AU g U ST 2 0 1 0 | VO l. Planning how to implement new functionality. we are actively prototyping Code Canvas. see Table 1. Developers rated these three among the most important to their job functions.5 how and Why Developers Diagram To better understand how professional software developers use visual representations of their code. we did a participatory design of a paper-based code map to allow a development team to design its content and appearance and to witness how it supported their conversations. 1.7 Finally. From this data.
  using a tool we developed for the purpose. colorized identifier fragments to aid visual searching (which we call concept keyword colorization). or by dividing lines. where each box represented some kind of software entity and each arrow indicated a relationship between two entities.2 Box-and-arrow diagrams were by far the most common representation. The final design was basically an architectural layer diagram sprinkled with types (white boxes) containing method signatures. such as representations of planned. This suggests that the code map should be shared among teammates so they have a common spatial frame of reference. and the vertical banding representing concepts that cut across architectural layers. Armed with this general knowledge. It closely followed the visual conventions we found in the earlier study. These visual conventions suggest a starting point for the design of a code map. From these studies we learned that it is possible to design a code map from a simple set of visual conven- figure 2. top to bottom or left to right. Generally. The oahu code map designed through team participation.000 lines of C#. We first had each developer separately sketch the Oahu project on a large piece of paper. boxes were arranged so that relationships flowed in a more-or-less orderly direction. The dashed rectangle is the map region shown in figure 3. Through this process we arrived at a design (Figure 2) that represented the code in a way that was meaningful to the team. such as UML (Unified Modeling Language). with a callout showing the map at full resolution. hung it in the developers’ offices. we incorporated types and method signatures reverse-engineered from their code. High-level groupings were indicated by surrounding boxes or curves. 52 comm unicaTio nS o f T he acm | AU g U ST 201 0 | VO l . Boxes were typically labeled. and then revised the drawing based on their feedback. For several weeks we repeated a daily cycle where we printed this drawing. what should the code map look like? We collected many examples of developers’ visual representations of their code and identified the visual conventions they used. At their request. Adjacency was sometimes used to indicate a relationship between two entities. Four of these sketches are shown in Figure 1.practice supplement their conversations. It also included some features that are not typical in architectural diagrams. but this was uncommon. 5 3 | NO. Next we synthesized into a master drawing the common features and interesting exceptions that appeared in the sketches. but nonexistent code (for example. we worked closely with a software development team called Oahu (a pseudonym) to develop a paper prototype of a code map. 8 . the empty white box beneath the mobile phones). Some of these diagrams made casual use of visual notations.3 These ranged from sketches on whiteboards to diagrams carefully made using a drawing tool. interviewed the team members for changes and reports of how they used it. We also looked at the visual conventions used by developers when representing code. but arrows almost never were.2 The Oahu team consisted of a few dozen people working on an incubation project of around 75. Designing a code map The question remains.
  which makes a code map the central metaphor of the development experience.practice figure 3. user interface designs.) We designed the look of the Code Canvas map based on our experience with the Oahu team. The callout in Figure 3 shows the 100%-level of zoom. the Code Canvas map shows types as white boxes. 8 | c om m u n ic aT ion S of T he acm . zooming code map. with the identifiers labeled using concept keyword colorization. The team’s response to the map was mixed. where the code file itself is displayed 53 AU g U ST 2 0 1 0 | VO l. Code Canvas places all of a project’s documents (code files. The user is able to place any box on the map through direct manipulation. focused on the upper left corner of the ui layer. (A video of Code Canvas is available at. but the type names and member names are shown at a readable size. Reminders. The code canvas version of the oahu map.youtube. Using the visual conventions from the Oahu map.com/ watch?v=tsFfyli2Y9s. The map includes two overlays: search results in yellow and an execution trace as a series of red arrows. maps at the center of the Development environment We’ve incorporated insights from these studies into a prototype user interface for Microsoft Visual Studio. The callout shows the result of zooming into a method to edit its code. tions. An important lesson from the Oahu research is that developers assign meaning to the spatial layout of the code. among others). among others) onto a panning. com/msagl) to provide an initial layout for new code maps and to prevent occlusion and maintain relationships as the user makes subsequent changes to the layout. Code Canvas uses a technique called semantic zoom to show different levels of detail at different levels of zoom. Code Canvas therefore takes a mixed initiative approach to layout.microsoft. At the 10%-level of zoom. in particular the upper lefthand corner of the UI layer (the area indicated with a dashed rectangle in Figure 2). Two new hires on the Oahu team used the map extensively as part of their “onboarding” process. Other team members had several criticisms.5 Rather than relying on tabbed documents and hierarchical overviews to navigate and edit the code. but Code Canvas also uses the MSAGL (Microsoft Automatic Graph Layout) engine (. called Code Canvas. the code itself is invisible because its size is less than a pixel per line. all stemming from the lack of interaction. We were able to address all these concerns in our Code Canvas. The user can zoom out to get an overview of the project’s structure and zoom in to view or edit code and other documents. Figure 3 shows the Oahu project loaded into Code Canvas. add call graphs to the map). The type and concept boxes are posi- tioned in Code Canvas in the same layout as the Oahu map. icons. studying and annotating it often. They wanted to tailor the level of detail and the element positions to the needs of the discussion to change the content for the task (for example. 53 | N O. The Oahu code map showed that a single map could represent an entire software project in a way that was meaningful to all the developers on the team. and with types organized into labeled bands (Popup Menu.
  Coleman.1 Code Bubbles’ strategy is to start with an empty canvas and add items as the user searches and browses the project. rayside.cfm?id=864034 © 2010 aCM 0001-0782/10/0800 $10. steffen.org/detail. His research group designs development tools in a user-centered fashion: they conduct studies of development teams to understand their work practice and prototype tools to improve that practice. Zeleznik. In Proceedings of the Conference on Human Factors in Computing Systems (May 2002). C. In a labbased evaluation of a previous version of our code-map design. In Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Cowmputing (sept. Code Canvas shows the call stack using a series of red execution arrows. G. Information needs in collocated software development teams. 6.acm. 5. In Proceedings of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (2007). 9. spatial layouts to keep users oriented. r. b. She zooms out to give Jim a tour of the parts of the code involved in the feature. J.org/detail. 8. When Joe asks detailed questions about the algorithms. adeputra.org Code Spelunking Redux George V. code maps will allow developers to be better grounded in the code. C. zooms out. Jane’s development environment shows an overview map of the whole project. Cheung. which looks exactly as she left it. Kaplan.00 | AU g U ST 201 0 | VO l .. G. Code bubbles: rethinking the user interface paradigm of integrated development environments. For a tour of Code Canvas’s features.. we believe making a code map central to the user interface of the development environment promises to reduce disorientation. Venolia. Jane then creates a second filtered canvas.cfm?id=1809426 The Woes of IDEs Jef Raskin. since she has been moving around both of them for years. deline.acm.acm.J. After exploring this way for a while. Venolia.cfm?id=1483108 Visualizing System Latency Brendan Gregg. eick. except here the search results and class diagram are automatically kept in sync and are persisted together..6 a well-known software visualization tool from the early 1990s). As on the HOME canvas. In contrast. d.. first in a skeletal form (in the style of Seesoft. deline. Karumuri. 2007). M. 4. Gina Venolia (. At intermediate levels of zoom the code becomes visible. G. Venolia. Its layout is as familiar to her as her hometown. Code Canvas: Zooming toward better development environments. focusing on the next generation of software development including software visualization and spatial layout of source code. Czerwinski.P. She clicks over to the HOME canvas tab.com/~rdeline) is a Principal researcher at Microsoft research. and points at parts of it to support what she’s saying.. de Volder. J. maintaining the spatial relationships that help her stay oriented.. deline. sHriMP views: an interactive environment for information visualization and navigation. Ko. 3. She zooms into one of them to look closer at exactly which classes are implicated and then clicks on an individual search result to look at the code itself.com/~kaelr) is a senior research software design engineer at Microsoft research. Joe knocks on the door and asks Jane a question. 957-968. let’s replay our initial story. To start her task of understanding her project’s dependency on the unsupported library. May 2010. sillito. In Proceedings of the IEEE Symposium on Visual Languages and Human-centric Computing (2006). deline. When the breakpoint is reached. IEEE Transactions on Software Engineering 18. In Proceedings of the 29th International Conference on Software Engineering (May 2007).J. These design goals are shared by the Code Bubbles project at Brown University.. In Proceedings of the International Conference on Software Engineering (New Ideas and Emerging Results). a. reiss. answer common information needs. Jane zooms in on the relevant code. best. rowan. Related articles on queue. 1992. M.. we will explore hybrids of the two approaches.. large-scale diagram to help developers stay oriented in their code. Neville-Neil. When the conversation with Joe is over. e.. s. This filtered canvas acts as the class diagram Jane previously drew on her notepad. M. Musen. whether working solo or collaboratively.com/~ginav) is a senior researcher with Microsoft research in the Human Interactions of Programming group. she is studying distributed software teams and developing systems that exploit spatial memory to support navigation and team awareness. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (May 2007). a.acm.. Code Canvas starts with an overview and allows users to filter down to items of interest.J. IEEE Transactions on Software Engineering... s.. K. Jane sets a debugger breakpoint and runs the program. conclusion Based the work practices we observed in our field studies. building an ecologically valid.l. 11 (1992). The HOME canvas is shared among all team members. Murphy. She immediately sees the two parts of the code that depend on the library. s. M. Spatial memory and reasoning are little used by software developers today. like those in Figure 3. In our future work. Jane simply closes the new tabs and returns to the one where she was working. focused on this call 54 com municaTio nS o f T h e ac m stack.. Ko. In Proceedings of the 32nd International Conference on Software Engineering (2010). working at the intersection of software engineering and humancomputer interaction.. seesoft: a tool for visualizing line-oriented software statistics. storey.. r. she decides to focus on just the relevant code. deline. bragdon. J.. The search results are overlaid on the map in yellow boxes (as shown in Figure 3) in addition to being listed in a separate window. sumner Jr. 7. s. drucker. robertson. F. she searches for uses of the library.. 8 . Her research focuses on building systems that make knowledge flow more freely among people. M.. Cherubini.. which provides the usual syntactic formatting and coloring and standard editor features such as code completion.microsoft. the code on the filtered canvas is shown inside boxes representing the relevant classes and interfaces..a. M. G. Robert DeLine (. litoiu. lanza.. Visualizing software systems as cities. r. References 1. Code Canvas provides explicit task support through multiple canvases and uses stable.. Kael Rowan (. In short. G. let’s go to the whiteboard: How and why software developers use drawings. We believe this will fundamentally change and improve the software development experience. r. and anchor team conversations. W.. Venolia.4 By exploiting these cognitive resources. a.. called the HOME canvas. C.. r.. then as readable text. laViola Jr.. Wettel. asking and answering questions during a programming change task. 5 3 | NO. Cherubini. r. J. J. Meyers. 10. M.practice using the standard editor. precisely to provide a common ground around which the team can have discussions.e. To explain the feature that is puzzling Joe. 2. K. we showed that developers form a reliable spatial memory of a code map during 90-minute sessions of programming tasks.org/detail.. so she creates a new “filtered canvas” in a new tab that contains the subset of the code containing the search results. Code thumbnails: using spatial memory to navigate source code. r.C. Michaud..microsoft..microsoft. His background has gone from operating system internals and formal software verification to modern user interfaces and HCI. 2008.. G.
  8 | c om m u n ic aT ion S of T he acm . leading providers and users of network virtualization technologies discuss how virtualization and clouds impact network service architectures.acm.org Leading experts debate how virtualization and clouds impact network service architectures. These new technologies promise to make applications more portable and increase the opportunity for more flexibility and efficiency in both on-premise and outsourced support infrastructures. By mache cReeGeR moving to the edge: a cTo Roundtable on network Virtualization how the advent of virtual machines and cloud computing are changing their world. 53 | N O. both in their abilities to move legacy applications to more flexible and efficient virtualized environments and to enable new types of network functionality. however. Before data-center managers can take advantage of these new opportunities.Doi:10. 1 78 72 5 1 Article development led by queue. —Mache Creeger 55 AU g U ST 2 0 1 0 | VO l. the geneRAL It community is just beginning to digest In this ACM CTO Roundtable. they must have a better understanding of service infrastructure requirements and their linkages to applications. Virtualization can break long-standing linkages between applications and their supporting physical devices.1145/ 1787234.
  networks have always been an obvious place to put things such as configuration state.practice clockwise from top left: Surendra Reddy. the implicit change to networking is that the last-hop switch is necessarily a feature of the hypervisor or hardware of the server and not a traditional hardware switch in the physical network. Now the leverage point is at the edge because the semantics there are very rich. Because of this. and so on. Networks in the past have reinforced the concept that user equals device. As a result people have never been required to produce good stand-alone network architectures. 8 PHotoGra PHs by toM uPton . Networks have never had to do that. Lin Nease is director of Emerging Technologies for ProCurve Networking. those identity relationships are now dead. I don’t require traditional 56 comm unicaTio nS o f Th e ac m | AU gU ST 201 0 | VO l . and I know when it joins and when it leaves. I would like each of you to comment on the challenges and opportunities people will face in the next couple of years as the world progresses with these new platform architectures. I know where a VM is. and charles Beeler. available service capacity. and past president of ACM. equals port. Juniper Networks. Inc. resource prices. I must have nice application platform abstractions. Workloads now move around. Mache Creeger (Moderator) is Principal of Emergent Technology Associates. neaSe: We’ve broken a paradigm. Martin Casado is VP. CTO of El Dorado Ventures. Hewlett-Packard. If I’m building an operating system that people use as a platform for applications. 5 3 | NO. the leverage point was in the network because it was central. mache creeger. Moreover. With virtualization. Yahoo! Charles Beeler is General Partner of El Dorado Ventures. martin casado. both in the ability to move legacy applications to more flexible and efficient virtualized environments and what new functionality may become avail- able. response time. given the progress of Moore’s Law and the large number of VMs (virtual machines) we can run per server. caSaDo: Networks have always been built in support of some other higher-priority requirements. Participants Simon Crosby is the CTO of Virtualization and Management Division. CTO. based on demand. cRoSBy: Virtualization challenges the binding of infrastructural services to physical devices. equals location. Be- cause the core can now handle so many workloads. Originally. virtualization as a separation layer has introduced a profound challenge to that premise. One can no longer reason about the presence or the utility of a service function physically bound to a device and its relationship to a specific workload. cReeGeR: Our discussion will focus on how virtualization and clouds impact network service architectures. dedicated network devices are not being asked to solve the same problem. Oliver Tavakoli is the CTO and VP of SLT Architecture and Technology Group. Steve Bourne is Chair of ACM’s Professions Board. Networking will need to evolve as a result. Surendra Reddy is VP of Cloud Computing. I know who’s on it. and founder of Nicira. As a result. While the networking industry was founded on a value proposition tied to a specific physical box. Citrix Systems.
  As IaaS (Infrastructure as a Service) comes into wider use. the dynamic changes completely. and VLANs are not virtualization in a global sense. Lin nease. service discovery and often don’t need multicast. address. cRoSBy: Deciding whether to buy an HP or a Juniper switch is a localized problem of scale. cRoSBy: Networking vendors sell differentiated networking value propositions to their customers. 53 | N O. caSaDo: Most scalable clouds are subnetworked. If I have an investment in IT skill sets to manage Juniper equipment in my private data center. After all. APIs will shift. 8 | c om m u n ic aT ion S of T he acm . It may be that the cloud vendor purchased equipment from a specific vendor. Juniper. value. and policies off-premise in the cloud? IaaS challenges the traditional vendor/customer roles for networking equipment. They are architected to not deal with VLANs (virtual LANs) or do flat anything and are not going to try and do one big L2 domain. I care about only the above-the-line result. Does this necessarily force commoditization in network equipment? I think it does. or whatever. and so forth. we make it difficult for application owners to support their rich needs for control. That’s way too hard if I already have a strong preference for and investment in a particular vendor’s equipment. I will have to go to a large number of cloud vendors and attempt to determine for my combined networking and compute problem how to choose the best vendor. configurations. and because the semantics are now more interesting at the edge. we could easily and authoritatively know things that used to be difficult to obtain. for example. its packaging. if we pursue a “genericized” feature list on the part of virtualized networks. When we started centralizing some of the functions that used to be distributed among many servers. complexity. It’s easier just to treat the entire network infrastructure as a big dumb switch and hold the intelligence at the edge because that is where the semantics are. IC integration. Alternatively. you have a clash of paradigms. Simon crosby. 57 AU g U ST 2 0 1 0 | VO l. Because the leverage point is at the edge. the richness of a switch/router feature set is designed specifically to address customer needs. It’s all subnet’ed upfront with the cloud overlaid on top. neaSe: We’ve seen the same process take place with blade servers. As the end user. To outsource that work. but there is no way for that vendor to surface its unique value proposition to the IaaS customer.practice clockwise from top left: oliver Tavakoli. or user—became much easier to determine because the new blade architecture made it very convenient. I want to specify SLA (service-level agreement). and deployment completely transparent. Things— for example. Google. we may not be able to support features in the cloud rich enough to meet customer needs. and management. in station state. ReDDy: In the next two to three years our goal is to make the building of an application. I don’t care if it’s Cisco. and Steve Bourne. If we genericize those features. Networks do not have virtualization built in. What I want is a service provider that constructs and delivers the network that is required. reportedly already builds its own networking gear from industry-standard parts. and x-megabit-per-second throughput and receive a virtual net- work that satisfies the requirement. latency. can I use those skills.
  here are the things I’d recommend. you lose visibility and control of those components. and do trending. and response time. they care about service availability and response time. can i use those skills. you are relying on the system. TaVakoLi: There are solutions today that will work in a garden-variety 5. Networks are being consumed into the host and they’re losing control. caSaDo: We all agree that if you take a slider bar and move it fully to the right to “future. provide security. decomposing it into constituent parts. I need to see everything in a holistic way: network. we want to build what is in effect a stateless. This has motivated operations teams to find ways to rent server cycles by the hour. neaSe: We are talking about taking a network function. At Juniper. How does someone decide on HP versus Juniper? Two or three vendors will come in and say.000-square-foot data center.” and that part gets separated into multiple parts depending on the specific attributes of your existing physical infrastructure. and any new server purchases will require their sign-off. 100. That’s how networks are rendered. stitch them into your existing environment. That’s one approach. high-capacity. From the service virtualization perspective.” you’re going to have some massive consolidation. The other is about the services received over the wire. We have to get to the same degree of homogeneity on the network side. provided that key enterprise requirements—SLAs and security and regulatory compliance—can be met. You can take the Cisco approach of replacing that virtual switch with your own virtual switch and pull everything back to an aggregation point. you move it only to a segment that supports the physical service. If I have an application running in a VM and move it from a server residing on LAN A to a server on LAN B. and that information is now more accessible to the guy who runs the host than to the guy who runs the network. You can also take a more specialized approach and address customers that have very specific needs such as latency sensitivity. 5 3 | NO. configurations.000-port switch but without backhauling everything to the Simon cRoSBy if i have an investment in iT skill sets to manage Juniper equipment in my private data center. neaSe: No. They take a general approach and are not as concerned about things such as endto-end latency. We are just figuring out how to get it back. A key opportunity arising from virtualization and the cloud is to enable CIOs to address the labor challenges of today’s owned infrastructure. TaVakoLi: One of the things that virtualization buys you is homogeneity. The question is how long will that slider bar take to get to the end result? cRoSBy: I talk to CIOs who are already telling their employees there will be no new net servers. depending on area. and eventually a few major winners will emerge. while leaving the virtual switch in place. and choosing a different place to implement those parts. ReDDy: There are two management perspectives in addressing this issue. and policies off-premise in the cloud? “god box” in the middle. In a medium-size enterprise I have a LAN segment called LAN A with an IDS (intrusion detection system). When you run on top of a hypervisor. cRoSBy: Let’s make it real. One is at the infrastructure level: the service provider who cares about the networks. and a different LAN B segment with no IDS. “I know the environment and I know what you’re trying to run. One of the parts is “figure out where to send this. 8 .practice neaSe: That’s looking at cloud computing in its infancy. service availability. We have a set of practices and tools that we use to monitor things. CIOs will absolutely take advantage of every opportunity to outsource new workloads to hardware they do not have to purchase and is automatically provisioned and managed without expensive labor costs. The question is both economic and technical: Who is best positioned to solve the massive network management problem? You could take virtual switches and. as Arista has done. Based on what you need. then I have a problem. storage. They don’t care about the network. 58 comm unicaTio nS o f Th e ac m | AU gU ST 201 0 | VO l . It will evolve over some meaningful period of time. you don’t really care what the drivers are.” Cloud vendors are not going to become a monopoly overnight. caSaDo: As you consume the network into the virtualization layer. computing. with a few large vendors left standing. Owning your own assets is still going to make sense for some time to come because the complexity of your existing data-center infrastructure will restrict what you can actually hire someone else to do for you as a service.
  caSaDo: This conversation gets much clearer if we all realize there are two networks here: a physical network and one or more logical networks. because someone comes in and says. and so on. but that sometimes requires gutting the existing architecture to pull off. then they will be locked into a vertically integrated stack and the world will pass them by. and snoop. learn. When they become a service. then you have to do it at the logical level. cRoSBy: The challenge for networking vendors is to define their point of presence at the edge. you have to put them into the logical topology or they don’t work. TaVakoLi: You can have a proxy at the edge that speaks to all of the functionality available in that segment. If distributed stuff involves more than one way that a problem could occur. caSaDo: It would have to be distributed on the box. it will be a world of know and cause. Though I have eight cores on a box. its specific policies can be enforced on that server. this causes me problems. It will not be a world of discover. Otherwise you are servicing the wrong network. 59 AU g U ST 2 0 1 0 | VO l. Moving current in-network functions to the edge (such as. nothing changes in complexity. They need to show what they are doing on that last- hop switch and how they participate in the value chain. It’s the only way you get back the value inherent in Moore’s Law. and that leaves seven cores unutilized. People usually don’t understand the infrastructure at that level of detail. Cisco. Today. so you already have virtualization. they should either not invest in anything now and wait a little while. there will be new interfaces that we’ve not yet seen. neaSe: The people who will be left out in the cold are the folks in IT who have built their careers tuning switches.practice cRoSBy: The key point is that you don’t have the luxury of being asked when a VM moves. If you do service interposition. storage. In this case you can’t do these VM moves without breaking the IDS. you want a switch without those affinity characteristics so you don’t have to worry about “same rack. The challenge is to incorporate the constraints that Lin mentions in the automation logic that relates to how/ when/where workloads may execute. This in turn requires substantial management change in IT processes. All my applications are very network-bandwidth intensive and saturate the NICs (network interface cards). however. You really want a huge switch with latency characteristics independent of row and rack. We need to schedule a variety of resources: network. That number is not just CPU utilization—memory and I/O bandwidth are also limited because there are only two network cards on the each server box. It is not true. you’re untethered. the service gets moved so the load is adequately resourced. 8 | c om m u n ic aT ion S of T he acm . You typically have more than one server. and that virtual switch is the last-hop point that touches your packets. Moreover. then it will cost more. you are told. and memory. something has changed. Think of virtual switching as a distributed policy enforcement point. neaSe: But once you distribute them. or invest in a scaleout commodity and make it look like Amazon. The virtual switch allows systems administrators to be in charge of an environment that can move workloads on the fly from A to B and requires the network to ensure that packets show up where they can be consumed by the right VMs. The argument that Lin (Nease) makes is that we would never move a thing to a LAN segment that is not protected. since I do not have a virtualized network. and address this problem? caSaDo: You either take advantage of the dynamics of the cloud. These networks are decoupled. then you will have the same amount of complexity. “I’ve got a very expensive box and I need to have high margins to exist. Where you can interpose into a logical network. The technology simply dictates whether you can have a dynamic infrastructure or not. If they do not take one of these two paths. You’ve got logically isolated components. for example. partitioned. neaSe: No. caSaDo: You already have the model of slicing. same row” to achieve latency targets. if I can get problems from more than one place. 53 | N O. How do I address that? How do I take the IDS that I have on my network today. cRoSBy: The last-hop switch is right there on the server. BeeLeR: If I manage the network within an enterprise and I’m told we just virtualized all our servers and are going to be moving VMs around the network to the best host platforms. End of story: it will move to the edge. It’s about getting all the data into the right place and making best use of the available resources. cRoSBy: The mandate to IT is to virtualize. Once you do that. you are told about it after it happens. You have the exact same complexity model. If you’re going to inject it to one or more logical topologies. As the edge moves into the server where enforcement is significantly improved. and when a VM executes on a particular server. or you don’t. If people want the dynamics and cost structure of the cloud. You are not asked if the move is OK. at some point in the future these services will become distributed. computational. You’re buying a server that has incredible capacity—about 120 VMs per server—that includes a hypervisor-based virtual switch. they’re part of a logical network and they can be logically sized. is already staking a claim at the edge and protecting its customers’ investments in skill sets and management tools. I can use only one. neaSe: It seems like you would benefit from an affinity architecture where the communicating peers were in the same socket. ReDDy: My server utilization is less than 10%. No algorithms exist to optimally schedule these media to maximize utilization. which means you can move it and you do scale out. not of the future. When the IT guy sees a load not being adequately serviced and sees spare capacity. we also make a lot of I/O calls to disk to cache content. thus. that distributed stuff is equal in cost to centralized stuff. the exact same management model. services are tethered to a physical box because of the sales cycle. then as network manager. which are in different default domains. and that’s the best place to have all of those functions. ReDDy: It is more of a scheduling issue.” As soon as you decouple these things. via its Nexus 1000V virtual switch. TaVakoLi: From our perspective. onto the server) gives us a way to ensure that services are present on all servers. you have to make sure that you haven’t created 25 things to manage instead of one.
  practice
  TaVakoLi: You want an extremely holistic view. You are asking where you put a VM based on the current runtime context of the hypervisor so you can maximize utilization and minimize contention for all aspects of data-center operations, such as CPU, network, storage, and others.-7.K., Switzerland, or Taiwan as needed. I can do all this through layer-7 routing (Apache proxy layer). TaVakoLi: This is a different solu-
  tion to the problem of large data centers and virtualization in the cloud. If routing intelligence needs to move up the stack to layer-7, then by definition you’re going to disenfranchise layers 2 and 3 2 and 3 or network fuzzingbased architecture will eventually emerge providing network-management edge control that will have an API for edge functionality, as well as an enforcement point. The only question in my mind is what will shake out with NICs, I/O virtualization, virtual bridges, among others. Soft switches are here to stay, and I believe the whole NIC thing is going to be an option in which only a few will partake. The services provided by software are what are of value here, and Moore’s Law has cheapened CPU
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  if people want the dynamics and cost structure of the cloud, they should either not invest in anything now; or invest in a scaleout commodity and make it look like amazon. if they do not take one of these two paths, then they will be locked into a vertically integrated stack and the world will pass them by.quality.
  Related articles on queue.acm.org network Virtualization: Breaking the Performance Barrier Scott Rixner CTO Roundtable: Virtualization Mache Creeger Meet the Virts Tom Killalea
  Mache Creeger (mache@creeger.com) is a technology industry veteran based in silicon Valley. along with being a columnist for ACM Queue, he is the principal of emergent technology associates, marketing and business development consultants to technology companies worldwide. © 2010 aCM 0001-0782/10/0800 $10.00
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  in the early years of commercial AU g U ST 2 0 1 0 | VO l.2 This standardization process also benefitted software buyers by lowering transaction costs and risks. standardization gave both producers and buyers of software a way to capture and black-box best practices by embedding it into the standardized components of the systems.37 In principle. By Jan DamSGaaRD anD Jan kaRLSBJeRG Seven Principles for Selecting Software Packages use of computers. There was no software industry in existence at that time.and XMLbased systems).15 As the software industry formed over the next few decades. still developed as unique systems for each organization. many organizations outsourced their software development to specialized software suppliers. software built on open standards allowed customers to source from any supplier that could supply software in accordance with open standards (for example. that is. 8 | c om m u n ic aT ion S of T he acm .Doi:10. Open standards meant that prices dropped and functionality was en63 ARound the mId-1950s. all software systems were developed in-house.1145/ 1787234 . Java.16 Next in the standardization process was a step away from proprietary standard systems that essentially locked customers to a single software producer to open software standards. Most software products were. as it was now possible to choose among a proven set of applications. 1 78 72 5 2 Everything you always wanted to know but were afraid to ask about the decision-making process. there was little standardization. The next step occurred when that software producers developed their own proprietary software in order to capture economies of scale in developing the software once and then selling it to multiple customers. 53 | N O. however. Moreover.
  we mean a set of fundamental ideas that summarize important insights in software package acquisition that are not (yet) embedded into the practice of buying software. Internet Explorer). and in the process. an almost universal office suite emerged. The aim of this article is to provide practitioners with a grounded set of principles to guide the selection of software packages.26 instead. Microsoft Office. that is. Some standard software packages require little adjustment on the part of the user before they can perform (for example. 8 . As a package is adopted by many. language support. while other software packages are mere tools or platforms on top of which specific functionalities required by the user can be implemented (for example. program parameters. thousands or even millions of different organizations. which resulted in a mass market for many software application types.8 Software became even more standardized. ERP systems). Open Office) or other types of nominally free software. 5 3 | NO. The principles are interdependent and together they form a whole that is larger than the sum of the parts. For example. Packaged Software Packaged software is a category of information systems for which all 64 communicaT io nS o f T h e acm implementations are essentially identical.8 Some setups of parameters may be common among several customers. Google Apps) are other examples of packaged software. how. Within an organization. While the core components of a package are identical across all user organizations. Similar to Klein and Myers’ argument. The software package may be configured or customized to make it fit with specific requirements unique to the concrete implementation. word processing software was no longer produced specifically for a particular profession or industry or nation. In addition. it forms a standard because the core components are identical across all of its installations. many local markets were annexed into global markets. the main functionalities are common to all adopters. software producers had enough resources to make their software even more general-purpose oriented with larger feature sets that were organized into a product. the growing importance of system interconnec- tions means the choice of software package has wide ripple effects for other parts of the organization whose software packages. Firefox21 or Internet residing systems (for example. the implementation into an individual organizational information infrastructure is usually configured in some manner to fit the requirements of the organization.15 When it comes to managing the process of identifying and evaluating packages. and so on) to suit special needs among customers. in which case the producer can offer standard solutions on top of which only site-specific con- | AU gU ST 201 0 | VO l . This is accomplished by setting program parameters.23 Until recently in the IS academic community.20. and which principles apply to a specific situation. such as.31 but open source systems (for example.19 the use of all principles is not mandatory. or building interfaces with other software systems.24 This has been despite the leading trend that organizations use “shrink wrapped” systems31 where the core functionalities of the software are identical across all implementations in dozens. implementations.22 For the purpose of this article.1. for example. Packages are often referred to as “commercial off-the-shelf” software. By principles. macro functionality. and interests may not originally have been identified or considered in the decision process regarding a new software acquisition. we define a standard software package as: a collection of software components which when combined perform a set of generalized tasks that are applicable to a range of users. These highly configurable general purpose software products came to be known as software packages. but in each case it must be judged whether. the IS academic community has been almost silent. there has been a tendency to focus on traditional studies of software development and implementation of large custom-made systems.17. The generalized software products could be configured in various ways (for example.practice hanced. installing add-on modules.
  vendors.35 For example. CFOs. The seven principles were derived empirically from a field study and from our understanding of software acquisition. To broaden our knowledge base. The interviewees were CIOs. For each principle we provide examples that illustrate its importance. and general managers. 8 | c om m u n ic aT ion S of T he acm . and we followed its software acquisition processes and standard choices over three years. we also carried out 34 interviews in 13 other organizations. The seven principles have now been presented and critically reviewed at numerous IT managers’ conferences. During the three years the nature of intranets changed from being home grown. and we are indebted to the participants for many of the examples that illustrate the principles. any organization that was using software in effect committed itself not only to a software product but also to a particular software producer’s continued ability to deliver new functionalities. The persons interviewed were five senior directors with knowledge of—and some power to influence—software acquisition.000 employees. historic data about system compatibility. and were deliberately chosen because of their high experience with software package selection processes. The field study was conducted using semistructured interviews. most of 65 IllustratIon by JaM es Ga ry AU g U ST 2 0 1 0 | VO l. Seven Guiding Principles for Selecting Software Packages Here.practice figurations need to be made. 53 | N O. The focal company had more than 50. to a situation where a few local software companies vigorously fought over market share. SAP for oil and gas). as organizational requirements evolved and new technology became available. The field study approach provided us with in-depth knowledge of a number of standards decisions made by actual organizations. to a situation where intranets were built upon international standards and readily available from multiple software houses. we present the guiding principles for making a better informed choice when selecting software packages. A second source of inspiration was information about particular software standards and packages. In the present day. Yet another source of inspiration came from participating in an industry network in the late 1990s where representatives from 60 companies met bimonthly to share their knowledge and experience with corporate intranets. Prior to the emergence of packaged software. the ERP producer SAP provides more than 25 industry solution portfolios for large enterprises that embed best practice (for example. The longitudinal approach meant that a theme identified in one interview could be further investigated and validated in subsequent interviews. market shares. The first principle we label the founding principle because it is fundamental to the other six. The fundamental first Principle: When you buy packaged software you join its network. All interviews were recorded and transcribed and thematically coded. and mergers and acquisitions.
  the network and package co-evolve. We shall not conclude the heated debate over open source here.10 which make risk mitigation activities even more central. government authorities and other compatible software products. the investment represents sunk costs. As the application type benefited its adopters. the organizational data and the | AU gU ST 201 0 | VO l . as they own the rights to the package outright and thus control its further development.20 Many application types have historically developed in an evolutionary manner.34 An organization’s purchase and implementation of a particular software package thus means that the organization has joined the network associated with the software package. where the first simple implementations were custom built by innovators. and so on). and configured by. In the network the distribution of power and influence depends chiefly on who controls the package and thereby its evolution. organizations must take a long-term perspective and envision a more complex and connected future. Open source packages. As an example of influence. and then spread to a small number of early adopters. Beyond the immediate network of users and producers. As the pace of change in the computer industry reduces the effective lifespan of most hardware and software to a few years. by reverse-engineering the package’s functionality. 5 3 | NO. but merely emphasise that organizations adopting a software package need to be alerted to the intimate connection between a software package and its associated network.29 Open source software can appear unattractive and risky to some because there is no central point of control from which advice about the software package and its future development can be sought. on the contrary. the software is designed specifically to promote shared ownership. It is imperative to choose to participate in the network that is perceived to provide the best long-term benefits as the organization. competing systems became available on the market. the extended network includes vendors. ful users has repeatedly postponed the sunset date of Windows XP. A similar evolution trajectory will likely describe the development of future application types that first appear as isolated systems. The network around the package has implications for the purchasing decision and has to be considered as part of the investment decision. The network indirectly also has other interests in common. for example. The users and producers of a software package constitute a network of parties that share a common interest in its destiny. the pressure from power66 communicaT io nS o f T h e acm The users and producers of a software package constitute a network of parties that share a common interest in its destiny. or else they risk implementing tomorrow’s legacy systems. Many choices made in the early stages of an organization’s use of computers have turned out to have surprisingly long-lasting consequences. as both software and data standards have been shown to be very persistent.25. To a large extent.34 The network is virtual. in the sense that the members probably do not know each other but nevertheless share a common interest in protecting their investments and ensuring the continued evolution of the package. are not owned by a single entity. 8 . Principle Two: Take a long-term perspective: Look ahead but reason back. and finally the application type became a commodity. Others view these properties as strengths since they protect the standard package from the opportunistic actions of profit maximizing software producers. for example. and the level of commitment is equal to the size of the investment (buying and configuring the software and the training of personnel. the training and education of personnel. the producer wields the greatest power over the proprietary software network. standard setting institutions. instead. many independent software vendors with the necessary competences and technical skills. possibly to be bundled with other software application types into larger software packages.practice these commitments and dependencies have evolved from local software producers to global standard software packages that can be sourced from. As a consequence. The producer’s power can be challenged if users unite to influence the producer or even challenge the producer’s ownership. In the case of most software packages. We emphasize this long-term perspective of software packages.
  enabling user organizations to choose among competing packages based on features such as price. the organization may find itself chained to the producer because the costs involved in switching to another package are prohibitively high. Shapiro and Varian34 argue that when buying standard technology we should look ahead but reason back. however. 8 | c om m u n ic aT ion S of T he acm . One historical example is the fight between Sun and Microsoft over Java and extensions to Java. and the organization is in effect locked-in. it becomes an insurmountable barrier to change.11 This is quite common for ERP systems where once the initial choice between (for example. and for the community in general. it is important to be aware that proprietary features that might be useful for the singular adopter are in fact false gold for the network at large. One route to mitigating the perceived risk in purchasing packaged software is to choose a package based on its historical and current success. meaning that it will be harder to pull away from the software package that embeds the proprietary extensions. 53 | N O. As standards and packages evolve and producers compete against each other. a package may be so successful in the market that there are few—if any—viable alternative products available to the organization. this development can be caused by legitimate technical design and implementation decisions.32 The practice of adding proprietary extensions to an (open) standard is successful when some adopters find the proprietary features attractive and implement them. In a similar manner. thus diminishing the value of a standard. as measured by the financial success of the software package’s producer and the size of the associated network. has been made.” and often Microsoft is associated with an almost flawless execution of the technique. blind alleys and one-way streets. an example of which is the current choice of operating systems for PCs being limited to Microsoft Windows.33 Of course. we describe two scenarios representing opposite outcomes of a competition between software packages. there is safety in numbers. thus doubling the throughput of the non-propri67 AU g U ST 2 0 1 0 | VO l. Below. In this situation. Sometimes software adheres to one common standard. For example. reaching or breaking compatibility. giving organizations the choice of staying with the incumbent producer or giving them time to look for migration paths toward a standard package with more perceived vitality. a By false gold or fool’s gold we mean something that appears attractive but in reality is not valuable at all. etc. Oracle Financial Systems and SAP). Most often. as reported by Chapman7 who narrates the story of how WordPerfect lost its near monopoly and how other software packages such as Netscape and dBase lost their lucrative position in the market. performance. noticing the network and the evolution process that produced it. standards often break down anyway as competitors extend the limits of the standard. Flocking behavior is a low risk strategy that is worth pursuing for software support of non-core functionality and for companies that consider themselves followers. compatibility is not a clear binary issue. it means that proprietary features become entrenched as de facto standards.12 The blind alley scenario refers to the situation where an organization has adopted a package that is losing its market share to competing packages. This is the case when the purchase of a particular package in effect obliges the organization to place future purchases with the same software family because the product has low compatibility with other families of software or packages. and even if such governance does exist. namely.practice standards that define them are more durable. but shrinking network effects make the downward spiral inevitable. Despite the sudden and remarkable development. David12 uses the term “angry orphan” to describe the situation of the losing package. This principle is useful to include when comparing a proprietary software package from a local vendor with that of a software package built upon an open global standard. We applaud and echo this advice that is valid also when selecting packaged software. There are some calls for the execution of this predatory business technique of “embrace. In a special case of the blind alley scenario. packages may converge or diverge on some features. Principle Three: When choosing packaged software. A producer may differentiate its package from the competition by adding proprietary features and unwarranted proprietary extensions to an open standard. usability. but it may also be caused by the producer’s perceived advantage in changing the degree of compatibility or interoperability with competing packages. Every time a proprietary feature is implemented it adds to the switching costs. the losing software package might undergo rapid developments. The break-down of open standards happens in many cases where there is no central governance of a standard by a central institution or authority. such as. sail boats never really challenged the inevitable change to steam engine boats. it becomes prohibitively expensive to switch.34 For the network.a Because of the long life expectancy of organizational data stored in some (often proprietary) format (see Principle Two). Principle four: focus on compatibility and beware of false gold.9 One example that we claim to be false gold comes from the company Linksys (owned by Cisco) which has extended its wireless network equipment with proprietary protocols. Sometimes. the losing package manages to capture a niche market network where it may sustain itself for years—or even perpetually.17 The one-way street scenario describes the situation where the organization is left with little choice when it comes to buying upgrades or expansions to the package. backward compatibility between software systems becomes a major factor when organizations consider new software investments. and extinguish. However monopolies are constantly challenged and they are often short lived in the software business. the greatest speed of innovation in sail ships happened as the steam engine challenged the sail as the leading propelling technology on sea voyages. creating a near monopoly. extend. He points out that such products often show a sudden rapid development when they are losing the battle. Only the law suits that doubtlessly follow spoil the perfection.5 An organization’s standard package choice therefore involves participation in networks that may last a decade or often longer. However.
  and if the proprietary extensions have become entrenched. organizations should be conscious of the adoption of proprietary extensions.11 One strategy is to produce free or low cost versions so that interested people will be more likely to sample it. the customization is often expensive and represents sunk costs that.23 If there is an unmet demand for knowledge and skills. in practice. the option to customize may appear shiny. Organizations should keep their options open by buying packaged software that is close to compatible standards. that is. In addition. does exactly the same thing.8. usually all customizations have to be re-implemented. Another variation is to make “academic versions” of the software package available as free downloads.5. the network has moved from a situation where organizations could choose to buy open standard compatible equipment from a number of independent suppliers to a situation where standard evolution has stopped and there is only one supplier of a proprietary de facto standard. limit the choices when the package or service contract is up for renewal. The result is disproportionately high costs for the people component of SAP implementations and delayed projects with reduced or poor functionality. both user and producer organizations suffer. such as a person’s rank in recommender-systems such as discussion Web sites. when upgrading the software to the next version. and consider which steps will be necessary to discontinue their use in the future.35 First of all. as is pointed out by Light. the network of organizations using a package is matched by a network of individuals competent in configuring and using it. When an organization chooses to use custom-built software.20 Second. enabling potential employers to retrieve an account of a person’s skills in regard to a particular software package. Producers employ various strategies for ensuring a pool of knowledgeable users for their software. a viable exit strategy.23. and if so.20. The co-development of the two networks (that of the producers and that of the users) has high path dependence to the point of being quasi irreversible. Such online networks also make it possible to determine the contributions of a particular member. For the adopting organization. 5 3 | NO. emacs. Beatty and Williams5 propose that an upgrade is an opportunity to review critically existing customizations in order to determine whether they are really needed.13 At the very least. it must carry the entire burden of training and retaining personnel to develop the necessary skills to use the software. and “Help for WordPerfect users” where the use of Microsoft Word was explained in terms that WordPerfect | AU gU ST 201 0 | VO l . unless absolutely necessary. Thus. where there may be no single trusted certifying institution corresponding to the owner or vendor of a package. the proprietary extensions of D-Link and Linksys are not compatible. Another large manufacturer. One historical example of misaligned networks is that of ERP systems. Linksys gives users a strong incentive to use Linksys hardware exclusively. or to bundle the package with textbooks used in educational institutions. the new features of the next version are obviously not part of the customization that was implemented from the previous version.30 Often local practices or cultural issues add to the desire to customize or localize the package. to determine if they are supported in the new version and eligible for elimination.22 Customization is different from configuration in that customization is more radical and adds functionality that was not an intended generic feature in the original package.11 For a new competing software package that starts with essentially no network. document their use in the organization. and if they are already using proprietary standard packages.11b. Microsoft sought to circumvent the knowledge barriers by providing WordPerfect users an easy passage.5. While the products are still backward compatible with the open standard backed by the IEEE.33 An alternative approach is to invest in building gateway features into the new standard package. Microsoft Word featured two gateways: an alternative user interface where Microsoft Word could be made to emulate the keyboard shortcuts of WordPerfect. however. The process of institutionalizing skills is more complex for packages based on open source (sendmail.13 When Microsoft Word was winning over the majority of the word processing market from WordPerfect in the first half of the 1990s. however. among others). we advocate avoiding any comprehensive customization of packaged software. they should keep their eyes open for gateway standards as a way to break an existing lock-in to a proprietary extension. Ideally. For the community. however.16.6 If the new package is proprietary and the owners are willing to invest. but often the supply and demand of certain skills is not aligned. In fairness. the risk remains. promises access to knowledge of the package’s application and implementation. Instead. In line with this.practice etary protocol IEEE 802. D-Link. none is willing to adopt the next open standard version. where the number of people with knowledge and skills of the configuration of SAP systems is far less than the demand from user organizations. it should be noted that neither D-Link nor Linksys has been successful in their effort to manifest their proprietary extensions as de facto standards. the existing network forms a formidable entry barrier that is difficult to break. Generic software packages do not meet all the requirements of an organization. 68 communicaT io nS o f T h e acm but for several reasons. could turn out to be false gold. other forms of legitimization are used. Instead.28 there are therefore plenty of options offered as part of the package to configure it as needed.8 Beatty and Williams5 recommend “un-customizing customizations” before any upgrade is attempted because they are found to form major technical obstacles and are the main threat to achieving a Return on Investment. The use of packages. thus easing the transition from an incumbent package.11n). Principle five: choose a software package with accessible knowledge. Linux. 8 . one way for the new standard package to achieve a critical mass of users is for the owner to bear some or all of the costs for the organizations willing to switch. the danger of proprietary extensions is that it may not be compatible with the next generation of the open standards (in this case IEEE 802. Customization is more lucrative for local software vendors compared to selling the package itself.
  By choosing an open standard. 53 | N O. an organization can usually choose between numerous compatible software packages. programming. or seeking to ensure access to the data from other information systems in the future. Referring to Web site design guru. 8 | c om m u n ic aT ion S of T he acm . according to its available resources and constraints. Dominant designs sometimes become static and end up as anachronisms when the surroundings change. and therefore prefer new Web sites to be designed similar to the sites with which they are familiar. we would thus not recommend this strategy for most organizational standardization issues. An everyday example is that the functionality of an electronic spreadsheet program can be employed by a word processing program to perform a calculation inside a text document. forward compatibility. Organizations can choose to standardize two types of skills: generic or specific skills.4 Interoperable information systems are able to communicate during the execution of a particular task. Standardization can be achieved at various levels and in many forms in packaged software. or if necessary. even though no files are ever saved to diskettes and personal computers no longer have disk drives. Here. the software package’s only compatibility restraint is that it must produce an output that can be used by recipient users or software. More advanced modes of standardization of data interfaces include interconnectivity and interoperability. Organizations may choose standardization of skills by employing only people with a particular education or skill set. the diskette icon featured in most software applications invokes the “save” function. Standardization of user interface is a common strategy employed to limit the need for user training. a dominant design typically emerges. AU g U ST 2 0 1 0 | VO l. and so on Specific skills encompass a user’s qualifications with a particular software package. Nielsen. thus bringing the simple advantage of choice.27 users spend most of their time on other sites.14 Features such as these will have far-reaching implications for the implementation of standard software packages and interorganizational information systems in the coming years. For example. We suggest using this principle to assess the available knowledge base for the software package. An organization might choose standardization of data structure for one of two reasons: seeking backward compatibility with data stored in legacy systems. such as critical thinking. This standardization strategy has the strength of allowing users greater freedom to optimize and personalize their production methods. to carry the cost of training new employees to some formalized level of training (see Principle Five). although both are also subject to standard deviations among the implementations from various producers. More advanced implementations allow interoperability between software running on separate computers .even in different locations or organizations such as most Web services organized in serviced oriented architectures (SOA). Generic skills are skills that are acquired through education. Examples of data standards with wide vendor support are the all-purpose information formatting languages XML and the database query language SQL. business knowledge. where different departments in an organization may use very different production techniques as long as their Web pages satisfy agreed-upon requirements. One example is that of Web page production. an organization can usually choose between numerous compatible software packages. Principle Six: choose packaged software with the right type of standardization. thus bringing the simple advantage of choice. and these may 69 By choosing an open standard. The disadvantage is that the user organization must abstain from using any proprietary features or extensions of the packages chosen (the false gold mentioned in Principle Four) in order to maintain strict data standardization. resulting in striking similarities of user interfaces among different software systems.practice users were accustomed to. that is. In standardization of output. The strategy also has serious drawbacks if the users ever need to share intermediate data. After some experimental implementations of information systems of a particular type. we provide an overview of the most common types of standardization because it is important to choose the type that is right for the particular organization.
  Second. we recommend organizations to follow and standardize in all non-core areas to bring down costs. the principles help IT managers ensure that vital aspects of the software package acquisition process have not been left out or neglected. and many are even updated on a continual basis. Finally. The proposed principles are useful in several ways. organizations must be prepared to lead (be an early adopter) and tolerate a higher degree of standard uncertainty in core areas. it may never be possible to find a perfect match. and in order to differentiate themselves. Second. adopt its predecessor today by joining its network. Companies should seek to select the package that fits their situation. activities such as conversion of legacy data may turn into considerable tasks. However. as there may be no personnel with expertise in both the legacy system and the new software package.practice be certified by the product’s producer or a trusted third party (see Principle Five). Here is a checklist that IT managers can consider in addition to the usual technical features and price. some buyers may assume a wait-and-see position. Principle Seven: all journeys start with a first step. there is little available advice on how to evaluate and choose among the offered packages. determine the necessary feature sets.3. It is therefore necessary to adopt a multilateral approach that asserts the benefits of participation from as many parties as possible in the selection process. the best strategy to ensure that a better package is there tomorrow is to 70 communicaT io nS o f T h e ac m We promote a view of buying software as a continuous process of constantly trying to match available packages with a base of already installed information systems. while anticipating future organizational needs and advantages in technology. while they let the rest of the market test out competing products. One might argue that if all are using the same standard software package. this strategy will mitigate the risks of investing time and money in a software package which later loses in the market. IT managers would have to spend much time condensing these foundations from available theoretical and empirical sources. while anticipating future organizational needs and advantages in technology. Being part of the network will also ensure that special needs are noted and incorporated into the next version of the package. First.20 Of course. conclusion Software packages are replacing custom built software at a fast pace.20 Therefore. Third. and thus it is very likely that while an organization is waiting for a package to appear in the marketplace for a perfect fit. Software packages are networked and built around standards that allow (and disallow) connection to other software systems and these considerations must be added to the equation. as other companies’ actions also contribute to the destiny of the package. First. This article highlights seven principles that are related to selecting and assessing software packages.36 After a prolonged sampling process and the organization finally selecting a software package. without the principles. In fact. but we advise organizations not to fall into the wait-and-see trap for the following two reasons. Yet. this is not a unilateral decision. 8 . so an organization stands a greater chance of finding software that fits its needs if it plays an active role in the selection process (invest in the package). In a market of fast update cycles and many options. forcing certificate holders to take new exams in order to preserve their status. and so on. the set of principles is an invitation to formulate a disagreement and start a discussion on what constitutes sound software acquisition practices. its requirements may have changed. 5 3 | NO. We promote a view of buying software as a continuous process of constantly trying to match available packages with a base of already installed information systems. a winner will only emerge when organizations actually buy software. too. The principles extend beyond the two obvious but narrow factors of price and immediate features. where does competitive advantage come from? As a rule of thumb. to include a wider networked and multilateral view of software packages. We will return to the issue of competitive advantage in the conclusion. the further development of packages is inevitable. when evaluating a software package purchase: ˲˲ What companies are involved in | AU g U ST 201 0 | VO l . they form a reference point for IT managers when engaging in software acquisition. Every major vendor in the packaged software market has such certification programs.
  . Another example of the application of the principles was the company in the field study mentioned earlier. C. sawyer. 1986. Chapman.dk) is director and a professor at the Center for applied ICt. G. an assessment of packageorganization misalignment: Institutional and ontological structures. 34. shapiro.r. should we wait? network externalities and electronic billing adoption. European Journal of Information Systems. Hawaii. Hawaii International Conference on System Sciences. open source movements as a model for organizing.. b. upper saddle river. J. 1999).W. J. C. Service-Oriented Architecture: Concepts. 214–222. competitive advantage is gained from being able to spot and adopt the packages of the future before they have become the de facto standard packages. and Myers. and louis.. 165–202. selling packaged software: an ethical analysis. (ed. nielsen. 18. a. and Varian. News. and light. 215–235. Technology.. l. d. and Varian. Khoo. and Wong. 1.). d. 195–210. 119–121. 1999). J. Growing systems in emergent organizations. locating packaged software in information systems research. European Journal of Information Systems 16. In Proceedings of the 12th European Conference on Information Systems. and network externalities. and lyytinen. M. 105–109. References 1. 568-583. Questioning the It artefact: user practices that can. besen.K. light. Information systems development: a market-oriented perspective.a. 2007.C.. 33. Clio and the economics of Qwerty. European Journal of Information Systems 16. P. narrow Windows. 24.. 1 (2002). stango (eds. Vancouver..J. r. Cincinnati. contingencies and dependencies. 2005). 2005. s. the art of standards wars.. sawyer. erP II: best practices for successfully implementing an erP upgrade. C. (turku. white and many shades of gray. Pollock. s. K.s. 2002. schuff. Ca. Commun. and bunn.M. 2. ljungberg. t. s. 2 (1994). California Management Review 41. 3 (2006). Finland. J. s. Information Economics and Policy 3 (1988). H.r. david. ACM 48. Ma. 5 (2007).d. Klein. and Green. In Search of Stupidity: Over 20 Years of High-Tech Marketing Disasters. deciding to upgrade packaged software: a comparative case study of motives.com. and bosco. 2001). Jan Damsgaard (jd. and Farrell. 35. could. 31.. Returning to the competitive advantage discussion initiated earlier and playing the devil’s advocate. evaluating interpretive field studies. 1998. nJ. e.C.. Chiasson. r. and Williams. Commun. the economics of Gateway technologies and network evolution: lessons from electricity supply history. 1 (1992). 16. ACM 45.a. M. 53 | N O.a. 5 (2007). Canada. The Information Society 17. and light. 2004). technological Innovation Project (no. However. 21. au. 2001). the university management decided that even though the package itself was free of charge.K. Karlsbjerg. C. 10). © 2010 aCM 0001-0782/10/0800 $10. 2 (1999). and cannot be supported in packaged-software designs. 3. the economics of advanced services in an open communications infrastructure: transaction costs. david. reflections on issues of power in packaged software selection. and soh. Ca. this research was in part supported by the danish research Foundation. West. Fitting standard software packages to non-standard organizations: the ‘biography’ of an enterprise-wide system. 26. Kluwer academic Publishers. adam. 2 (2001). “In the world of software packages.a. b. (Hawaii. Cambridge university Press. and light. Greenstein and V. ACM 42. The Cathedral and the Bazaar: Musings on Linux and Open Source by an Accidental Revolutionary. and Design. 101-106. 8–32. advantage comes from having the same packages as everybody else before they do.00 AU g U ST 2 0 1 0 | VO l. r. apress. Commun. 1–19. Kanellos. ACM 44. Information Rules: A Strategic Guide to the Network Economy. 151–165. H. Hawaii International Conference on System Sciences. n. erl.r. raymond. Pinnaflex educational resources. and Procter. 117–131. 317–332. MISQ 23. 11. r. r. 2 (1985). david. attewell. and Kauffman. 6. b. 1997. david. production costs. ACM 49 (Mar. Technology Analysis and Strategic Management 15. M. M. 27. J. Cambridge. o’reilly. J.” Thus. 155–178. 5. r. baskerville.a. y. grant number 331958. 2000. To illustrate. user interface directions for the Web. 2000). one might argue that if everybody were using the same software packages.com) is an associate product manager at active Community solutions. stanford university. M. 1999. P. where would competitive advantage in the form of differentiation come from? Succinctly put as a paradox. Germany. 1998. Potential pitfalls in packaged software adoption. d. 3 (2001). P. but when the network was deemed inadequate.d. J. and scheepers. In Proceedings of the 13th European Conference on Information Systems (regensberg. r. 5 (2007). denmark school of Information systems. Prentice Hall. 32. 15. and angry orphans: the dynamics of systems rivalries and dilemmas of technology Policy.s. J. and robey. boston. and sawyer.17 An illustration of Principle Five and Six is as follows: One large manufacturer had already implemented one ERP system when a vendor offered a competing ERP system at a very competitive price. berkeley. The manufacturer attempted to switch but after more than a year of attempting to implement the new ERP system the manufacturer had to revert to its old ERP system. Commun. 2001. 555–567. Commun. 28. 29. Copenhagen business school. Jan Karlsbjerg (jan@jankarlsbjerg. 527–530. Infor 25 (1987). P. staying outside the mainstream: an empirical study of standards choices. Klein. 23. George. sia. 36. using the seven principles. d. truex. end user computing and office automation: a diffusion of innovations perspective. Harvard business school Press. Howcroft. 2003. Karlsbjerg.W. australia. the economic realities of open standards: black. 19. 332–337. 97–102.. (dec. 13. 1 (Jan. 17. and denmark.caict@cbs. 117–123. H. shapiro. Framing the Domains of It Management: Projecting the Future through the Past. s. 8 | c om m u n ic aT ion S of T he acm 71 . b. damsgaard. 8 (aug. 255–277. European Journal of Information Systems 16. 67–94 20. the supporting network around the package was too local and too small for the university to invest in encoding the remainder of its buildings into the package. 2006). Information Infrastructure and Policy 4 (1995). 25. 8. W. Information Systems Journal 16. 65–72. 5 (May 2005). The American Economic Review 75.P. and to identify and phase out the packages of the past before they become legacy systems. Choosing how to compete: strategies and tactics in standardization. P. 4. The Progress & Freedom Foundation. 22. Commun. J. 37. Kutar. sun and Microsoft settle Java suit. it was decided to switch to the dominant package. dC. Organization Science 3. H. 7. bailey. b. 14. J.practice producing the package? ˲˲ How many companies are already using the package? ˲˲ How many software companies can configure the package? ˲˲ What is the history of the package? ˲˲ Is the package built upon open standards? ˲˲ How is the fit with other packages? ˲˲ What kind of standardization does the package represent? ˲˲ Is customization of the package necessary? ˲˲ Is there an accessible knowledge base for the implementation and exploitation of the package? ˲˲ What are the costs of switching to an alternative package? ˲˲ What are the implications of postponing a decision to adopt? In what direction is the package evolving? And is our company headed the same way? The principles can be used prior to making an investment and be used to monitor the vitality of existing packages. 12. Standards and Public Policy. oH. 3 (2003). shankland. and Klein. when a university built a new campus building it came with a free proprietary facility management system with the new building already encoded. Williams.. 542–554. s.. effects of conflict on packaged software development team performance. 30. Microsoft’s use of zero price bundling to fight the browser wars. Managing your total It cost of ownership.) The Origins of Software: Acquiring Systems at the End of the Century. Finland. 5 (2007). technology diffusion and organizational learning: the case of business computing. The skill set and knowledge base built around the former ERP system in practice inhibited a switch. H. J. s. Journal of Economic Perspectives 8. Ma. b.M. light. Washington. a taxonomy of Intranet Implementation strategies: to make or to buy? Journal of Global Information Management 11. l. European Journal of Information Systems 16. damsgaard. 10. McKnight.s. 9. blind Giants.F. The question was straightforward: Was the network of users around the software package sufficiently large to provide the package owner with revenue that allowed it to invest in developing the package? For a number of years the answer was positive. 3 (2003). Information Systems Journal 11. ACM 42. J. Moore. the role of intermediating institutions in diffusion of electronic data interchange: How industry associations in the grocery sector intervened in Hong Kong. 11 (nov. beatty. exploring cultural issues in the packaged software industry: a usability perspective. Inc. Curtin university of technology. The company used the principles to annually monitor the decision to stay with a package that had been dominant but was losing market share.
  as they are today. IllustratIon by st udIo to nne Safe modern programming languages promise significant benefits for constructing high-performance systems. but system software has evolved much more slowly. In the 1960s. Specification and verification are increasingly common for language features and library interfaces. Extensive sharing of code and data was essential for efficient use of scarce memory. not in high-level programming languages. 5 3 | NO. Despite advances in programming languages and tools. and Systems should be self-describing at all levels of abstraction. perfect software remains a vision for the future. as systems consist of many components. enabling principled decisions about system architecture. memory capacity. leaving a wide gap between system requirements and capabilities. they were not central to anyone’s personal life. modern programming languages let Microsoft rethink the architectural trade-offs in its experimental operating system. the small group of people with access to computers understood the technology and tolerated its shortcomings. They prevent entire classes of critical errors (such as those enabling buffer overrun attacks) while facilitating development and use of accurate and efficient software-development tools.contributed articles Doi:1145/ 1787234. However. and system architecture.9 Answering is important. . expensive devices used only by small groups of highly trained experts. Applications and systems were generally written in assembly language. Construction of the Singularity operating system began in 2004 with three design principles: Use safe high-level programming languages to the greatest extent possible. Software failure should not lead to system failure. and storage forced designers and programmers to be parsimonious with resources. However. robust system architecture can limit the consequences of a failure and give a system the ability to respond and recover without having to reboot. and thus operated in secure environments. Introducing specifications at the boundaries of components describes both their dependencies and their contributions to the system. By JameS LaRuS anD GaLen hunT The Singularity System at Microsoft Research began by asking what modern operating-system and application software would look like if it were designed with modern software-engineering practices and tools. Though computers were increasingly important in business.1787253 Safe. t h e s Ingu LARIt y pRo Je c t 72 comm unicaTio nS o f T he ac m | AU gU ST 201 0 | VO l . Systems must be self-describing at all levels of abstraction for building automatic tools that verify and validate their correctness and integrity. Moreover. Computers and the computing environment have changed dramatically since then. 8 computer users and uses were also very different. most are never formally described. computers were limited. None of these characteristics is true today. key insights new demands on computer systems require rethinking assumptions concerning language. Their limited speed. since almost every system today shares a common intellectual heritage with the time-sharing systems developed in the 1960s and 1970s. operating system.
  8 | c om m u n ic aT ion S of T he acm 73 . 53 | N O.Cred It t K AU g U ST 2 0 1 0 | VO l.
  not hardware mechanisms. or SIPs. and memory is reclaimed only when no longer in use. class library app. and support for hardware standards like ACPI). not present in C. | AU g U ST 201 0 | VO l . in a safe language. a program does not create or modify memory references. safe languages rely on garbage collection to reclaim memory. Due to the lower cost of isolation. resides in processes outside the kernel. rather than silently failing and permitting an attacker to inject malicious code. pointing the way to systems better able to respond to future computing requirements. Unlike Microsoft Windows and Unix systems. Unlike other microkernel systems. F#.a Moreover. as it has no GUI and only a sparse set of user applications. relieving programmers of having to devise and enforce conventions concerning when an object is no longer in use and which component has the obligation to free the object. 5 3 | NO. and other languages. Unlike in other systems. it follows a microkernel design philosophy in which much of a system’s functionality. class library subsys.5KLOC but only 1. Singularity is able to detect and avoid conflicts among components and prevent or isolate the use of unsafe code. Although the Singularity kernel includes many features found only in production OS kernels (such as multiprocessor support. class library driver class library runtime kernel aBi runtime runtime runtime security subsystem memory manager directory service manifest binder debugger and diagnostics i/o manager kernel kernel class library hardware abstraction layer runtime Singularity differs in significant ways from most previous operating systems. for example. that rely on language safety. full-feature kernel debuggers.contributed articles figure 1. also unlike other systems. 8 . all user code in processes—outside the OS-supplied runtime—must be written in a type. Safety ensures a program applies only operations appropriate to a particular type of object to instances of that object. Singularity is not a replacement for Windows or Linux. The counterpart hardware-abstraction layer in Windows includes 25KLOC of unsafe C and assembly. Conceived as an extensible home server. Due to the additional information provided by manifests and specifications. In addition. C++. channels content extension software isolated processes HTTP server TCP/IP stack network driver ext. Safe Programming Languages Modern programming languages (such as C# and Java) are type and memory safe. including its device drivers and major subsystems. C#. Singularity can require an extension (“plug-in”) to reside in its own SIP that prevents the extension’s failure from affecting its host SIP. Structure of a Singularity system. help detect programming errors that could have serious consequences. SIPs provide isolation and failure containment at far less performance cost than hardware mechanisms.700 lines of unsafe Sing# and 350 lines of assembly code. Singularity has been used primarily as a research vehicle to investia The hardware abstraction layer in Singularity consists of 21. processes in Singularity are software-isolated processes. input that overwrites a string buffer causes a runtime exception. so they can be used in more places than conventional processes. to isolate system software components from one another. a dialect of C#. 74 com municaTio nS o f T h e acm gate new OS abstractions. These properties. Figure 1 outlines the architecture of a Singularity system.and memory-safe language (such as Sing#.) Singularity also assumes more authority to decide which system components can be safely loaded and executed. or even Visual Basic). most Singularity code is written in safe high-level Sing#. (We describe later how hardware protection can be combined with SIPs in Singularity to provide multiple layers of protection.
  x64.4 Singularity’s approach differs in that it isolates a process’s objects by memory pages. memory-footprint reduction due to tree shaking.6. with one semantics if a program obeys the language rules and no guarantees if they don’t. not a large runtime environment like the Common Language Runtime (the virtual machine component of Microsoft .static lib c++ . This operation is prevented by Sing#’s type system for inter-process communication. and Java. it also depends on language safety to isolate OS extensions running in the kernel’s address space. Singularity quickly reclaims the process’s memory pages.731 Kb 2. Moreover.846 Kb code (Tree Shake) 1. Lisp Machines.w/ Gc — — 408Kb freeBSD 5. and Pass a reference to another process’s page. Language safety is another foundation of Singularity’s SIPs. program-analysis tools are not put in the untenable position of assuming a buggy program plays strictly according to the language definition. When a process terminates. which consist of memory pages holding the objects a process can access (see Figure 2). The common belief is that safe languages are inefficient. glorified assembly language like C or its more sophisticated cousin C++. rather than allocating them in a common address space. Language safety guarantees that code running on Singularity cannot perform either of these operations. Other systems. Table 1 emphasizes this point by outlining the memory footprint for a small program written in C. including Cedar/ Mesa. Safe languages are far more popular since the introduction of Java but are generally considered inappropriate for systems code. The program outputs “Hello World” using the standard I/O libraries and APIs for each system— printf for C and C++ and Console. code (Total) Singularity kernel Web Server SPecweb99 Plug-in iDe Disk Driver 2. and C# running on several different operating systems. which is usually written in a low-level.static lib c# . Much of the code and data “shaken” out of these programs comes from the unused portions of general-purpose libraries. unlike languages like C.contributed articles Furthermore. Singularity enforces the invariant that a reference manipulated by process P1 cannot point to a page belonging to process P2. because safe languages have a fully defined semantics. vs. Table 2 outlines the reduction in memory footprint Bartok achieves for a variety of programs. Beyond the performance benefits of improved memory locality and a simplified garbage collector. the isolation invariant is far easier for the operating system to Table 1. 53 | N O.371 Kb 2.NET) and the Java Virtual Machine. WriteLine for C#. 350KLOC). The C# code on Singularity is smaller than for all but one other system—the statistically linked code on Free BSD—in some cases half to one-third the size of C++ code. roughly the same as the C runtime in the latest version of Windows (72KLOC). memory footprint for “hello World” process (in kilobytes). The Shared Source Common Language Infrastructure runtime and class library are more than five times larger than the Bartok runtime (64 thousand lines of code. rather than turning to garbage collection to reclaim memory. A process might try to violate this invariant in two ways: Create a new reference or modify an existing reference to point to another process’s page. While the SPIN operating system uses traditional page-based hardware protection between processes. due in part to the size and complexity of their runtime systems and reliance on garbage collection.216Kb — 544Kb 572Kb 3. Bartok is a highly optimizing compiler that generates high-quality code and reduces memory use through extensive tree shaking to discard unneeded class variables and method definitions. Singularity’s Bartok compiler provides language safety without the typical performance penalty by compiling C#’s Microsoft Intermediate Language representation to native (x86. or KLOC. Singularity process objects reside on a dedicated collection of pages. where P1 ≠ P2. Bartok also links compiled code to a small runtime consisting of only a class library and a garbage collector. were written in higher-level languages and depend on language safety to isolate different computations running in the same address space.291 Kb 765 Kb 502 Kb 455 Kb % Reduction 46% 72% 77% 75% figure 2. Singularity c . Process 1 Process 2 Process 3 channel 2 1 3 exchange heap AU g U ST 2 0 1 0 | VO l. or ARM) code at installation time rather than at runtime.11 (Red hat fc4) Windows XP (SP2) 232Kb 704Kb — 664Kb 1. 8 | c om m u n ic aT ion S of T he acm 75 . C++.3 Linux 2.144 Kb 1.750Kb Table 2.
  hybrid hardware-software isolation using SiPs and domains.3 Linux 2. the system-configuration manifest specifies which SIPs reside in which domains. An extension’s failure typically causes the host to fail as well. Plug-ins (such as device drivers. for example. a plug-in that uses undocumented functionality can frustrate backward compatibility as a system evolves.6.300 719. except.11 (Red hat fc4) Windows XP (SP2) 1. in the worst case.340 figure 3. a car does not stop running when a headlight burns out or a tire goes flat.000 878 911 13. Singularity also provides flexible hardware-based process isolation as a secondary mechanism. Domains allow untrusted code to be isolated behind conventional hardware-protection mechanisms while more trusted code resides in the same address space. Orgovan and Tricker reported11 that approximately 85% of the Windows XP kernel crashes they studied is caused by device drivers. Considerable evidence shows that extensions are less reliable than host code.000 627 753 6. but the host has no way to prevent its use. by hiding names and documentation. browser extensions.000 91 346 803 freeBSD 5. Although less intellectually appealing than flawless operation. The epitome of this problem is the common plug-in software architecture that allows extensions to be dynamically loaded into a host’s address space.030. thereby allowing the system to detect the failure and recover by restarting the failed component. This recovery is feasible in many cases because of three built-in Singularity design decisions: SIPs are inexpensive. the extension is limited to the functionality explicitly provided by the parent process. Singularity Process create and start minimum kernel aPi call Thread context switch message request/reply 353. rather than word level. If the extension fails. seemingly unrelated changes to the host can affect the plug-in and produce many failures despite extensive testing regimes. By contrast.1 The basic cost of software isolation is the runtime checks for null pointers and array accesses (4. A process that wishes to invoke an extension starts the extension code running in a separate SIP. At runtime. and dynamic code loading. 8 . the system itself. Basic cost (in cPu cycles) of common operations between isolated processes on an amD athlon 64 3000+ system. A plug-in can use any data structure or procedure it can discover.7% of CPU cycles). Domains can run in either user or kernel mode (ring 3 and ring 0 on an x86 processor). Tight coupling between components in monolithic software systems routinely means the failure of one component can bring down an application and.10 The cost of creating a SIP and communicating between two SIPs is low in terms of CPU | AU gU ST 201 0 | VO l . SIPs are sealed processes that prohibit shared memory.380. benefiting from faster communications and failure isolation (see Figure 3). and spell 76 comm unicaTio nS o f Th e acm Table 3. most complex artifacts share this paradigm and most programmers are comfortable with it. 5 3 | NO. hardware isolation similar to conventional operating systems (separate address spaces and protection domains) incurred a cost of up to 38% of CPU cycles (see Figure 4).800 5.contributed articles enforce at a process level. Singularity assumes that software contains bugs and consequently is likely to fail occasionally. Unless the system formally specifies the interface between a plug-in and its host. Moreover. for example. A Singularity hardware-protection domain is an address space holding one or more SIPs. The Singularity architecture avoids many of these problems. but the parent process continues and can recover from the error. modular System architecture Unlike many systems. Most of a host’s functionality may be private or inappropriate for plug-ins. and Chou et al. in-process code generation. Singularity’s architecture aims to contain the consequence of a failure within a fault-isolation boundary. Domains also enable Singularity developers to run a series of experiments comparing the execution overheads of software and hardware isolation. Moreover.000 437 906 5. For example. code extensions can subvert modularity and engineering discipline. reported that the Linux drivers they studied have up to seven times the bug density of other kernel code.5 Plug-in architectures also involve other disadvantages: First. perhaps. sIP Unsigned App2 Protection domain ring 3 ring 0 App1 Signed extension Unsigned extension Unsigned Driver Signed Driver Kernel checkers) share their host process’s address space and have unconstrained access to its code and data structures. its process terminates.
  float. when a process fails.60 0. the following code is part of the contract for a channel to Singularity’s TCP service. Each channel is annotated with a specification.contributed articles cycles. DoneReceiving? -> SendOnly. .3% +33.0% +37. These operations are far less costly on Singularity. Channel contracts clearly require forethought for designing and specifying an interface. defining the legal messages that can arrive at the service when a socket is connected: public contract TcpSocketContract { . and pointers to other structures sent in the same send operation. Process 1 Process 2 Process 3 … Page 23 Page 24 Page 25 Page 26 Page 27 … AU g U ST 2 0 1 0 | VO l. Singularity’s compiler statically checks the code that sends and receives messages on a channel. } state ReadResultPending : { Data! -> Connected. SIPs do not share memory.7% figure 5.40 0.00 SiPS without runtime checks SiPS in physical memory Web server in SiPS in one separate virtual memory address space address space all SiPS in Web server in separate ring 3 address space address spaces +18. DoneSending? -> ReceiveOnly. as code cannot distinguish communication in which a message is copied from communication in which a pointer to the message is passed among the SIPs. One objection to SIPs and channels is they make writing software more difficult than shared data structures and procedural APIs. message exchange across a channel. Data structures shared between two processes provide a simple. which is a good thing. for example. progressively adding hardware address-space protection. 8 | c om m u n ic aT ion S of T he acm .. the service receives a Read message from a client. our experiments ran on a 1. normalized execution time comparing the overhead cost of software and hardware process isolation mechanisms for a Web server running on Singularity. By forbidding shared memory. unsafe code Tax 1. starting with a pure software-isolated version of Singularity.9% +6.. supporting the conservative assumption that the first process left the shared structure in an inconsistent state. ensuring it obeys the contract. programmers are able to encapsulate small extensions to existing applications or to the system itself in their own separate SIPs. The high cost of processes on other systems encourages monolithic software architectures and plug-ins to extend system behavior. On Singularity. RemoteClose! -> Zombie. the contract transitions to the ReadResultPending state. 77 figure 4. it relinquishes ownership of the message and can no longer access it (see Figure 5).9% Safe code Tax –4.8Ghz amD athlon 64 3000+ system. thus reducing the overhead of this isolation mechanism and allowing it to be used at finer granularity than a conventional process. A message is a structure consisting of scalar types (such as integers. In practice. When a SIP sends a message across a channel. For example. and strings). Table 3 summarizes the cost in terms of CPU cycles of a variety of systems for creating a process and communicating with the kernel and another process. where the service is expected to respond with a packet of data or a status or error indication.40 1. Messages are allocated in a special area of memory—the Exchange Heap—with programs accessing it through a special Sing# type system that permits at most one outstanding reference to a data structure. Close? -> Closed. message ownership passes from Process 1 through a channel to Process 2. NoMoreData! -> SendOnly. arrays of structures. or “contract. the shared structure couples the failure to the other process. } If..” of the content of each message and the allowable sequence of messages. However. 53 | N O.20 0. This semantic prevents SIPs from sharing the memory in a message while allowing for efficient communications. and Communication between SIPs passes through strongly typed channels. Singularity ensures that process state is altered by only one process at a time. The receiving SIP should still validate message parameters but need not worry about their asynchronous modifications.7 Shared memory further opens each process to spontaneous corruption of shared state at any time by an errant or malicious peer. state Connected : { Read? -> ReadResultPending.80 0. high-bandwidth communication mechanism requiring little forethought on the part of the host.20 1.00 0.6 A channel is a pair of bounded message queues between two SIPs. Write? -> WriteResultPending. GetLocalAddress? -> IPAddress! -> Connected. GetLocalPort? -> Port! -> Connected. Abort? -> Closed..
  described earlier. including SLAM2 and Boogie. Benefits include SIPs for encapsulating program components. These pre-populated I/O objects simplify driver access to hardware while simultaneously providing low-cost access to hardware resources with language safety. Documentation grows stale in the absence of systematic tools to detect discrepancies between a description and the related code. as well as on low-level interfaces. . Another example of high-level specification is device-driver 78 comm unicaTio nS o f Th e acm | AU gU ST 201 0 | VO l . explicit contracts.3 generally check the behavior of procedure and method boundaries. Designing the interface to the allocator appropriately in the first place could reduce the communications cost and overhead penalty. Singularity may corroborate only a subset of this information. 8 unlike in other systems. but it uses the declared information in the following ways to ensure correct system configuration: Look for conflicting claims. pointing out discrepancies between the behaviors. capture the behavior of Singularity’s primary communication mechanism. On the other hand. specifications that drive tools remain closely linked to code and must meet only the lower bar of providing sufficient utility to justify learning a new language and unfamiliar tools. Still. While the proper use of these interfaces is central to writing correct software—and strongly supported by Singularity. the Singularity kernel starts each device driver in its own SIP. processes in Singularity are software-isolated processes. Because its interface originated in a shared address space. it passes a large amount of data—50KB– 1. that rely on language safety. including for purposes other than staticdefect detection. When starting up. we removed one of the Bartok compiler’s most complex components—its register allocator— and ran it in a separate SIP. If the system detects no conflicts. running every time a function is compiled. 5 3 | NO. It shared code for 156 classes with the rest of the compiler. Nevertheless. configuration of system components by manifest. When a driver is loaded. The correctness of a system depends on them. Such tools. to isolate system software components from one another. Singularity looks for conflicting claims on hardware resources.5MB—at every invocation. and the modified compiler ran only 11% slower while compiling the Singularity kernel. Singularity demonstrates that lightweight specifications are valuable if closely connected to the underlying system and offers a value greater than the additional burden they impose. Discussion The Singularity project is first and foremost an experiment in building from scratch a nontrivial system (approximately 250KLOC) using a safe language. Singularity follows this paradigm of specification and checking at many different levels of system structure. and compiler checking reduces the burden of this style of development. or SiPs. Depending on hardware support. As an experiment. Self-Describing Systems For the past 10 years. software-development tools based on formal methods have become increasingly sophisticated and available8 for comparing a specification of the intended behavior of a system component against the component’s actual code. and many ideas have been transferred into Microsoft products.25% of the compiler). the experiment shows the practicality of partitioning even a complex interface so it works across channels. much of which is the same across allocator invocations (such as the machine description). including language support for the Boogie verification system— systems provide many other abstractions. Much of what we have learned may be of value in other systems. manifests.contributed articles programming language support for communications. Channel contracts. Specifications may be closely tied to the actual code. and Incorporate declared resources. then Singularity incorporates its declared resources into the system manifest used to configure the boot process. It also creates in-process I/O objects for accessing the I/O registers and interrupt lines used by the driver. we were able to run the allocator in a separate SIP by changing 508 lines of code (0. not hardware mechanisms. then Singularity avoids a conflict by refusing to load the new driver. If a new driver uses the same I/O registers as an existing driver.12 A Singularity device driver specifies the underlying hardware resources (such as memory mapped I/O registers) it can access.
  and rajamani. Derrick Coetzee. and future research should aim to help resolve three troubling issues: the garbage collector in the kernel.contributed articles and a lightweight.. an empirical study of operating systems errors. new york. mind. In Proceedings of the Fourth International Symposium on Formal Methods for Components and Objects (amsterdam. and Dan Simon developed the security architecture. seeking performance to the detriment of essential system attributes (such as modularity and reliability).. Mark Aiken. In Proceedings of the First ACM SIGOPS/EuroSys European Conference on Computer Systems (leuven. M. 2005. P. M.com) is director of research and strategy in the extreme Computing Group at Microsoft research... Fähndrich. and levi. 2 (apr.). Despite early concern in the project and ongoing external skepticism.K. bowen. and Wobber. springer. and hands to the project. eggers. new york. M.. 2008). 177–190. 2007). aCM Press. ball. aiken. b. dec. roeder. manifests could be used in more traditional operating systems to describe dependencies.). J. Our experience confirms wisdom in the Java and Common Language Runtime communities that garbage collection obviates the need for strict memory accounting but does not eliminate the need for carefully managing memory in highperformance code.-y. and is governed by strict rules restricting references. 8 | c om m u n ic aT ion S of T he acm 79 . orgovan. s. 53 | N O. s.. M.com) is principal researcher in the Microsoft research operating systems Group and leads the Menlo project and the singularity project at Microsoft research. t. redmond. larus. In Proceedings of the 13th Conference on ComputerAided Verification (Paris. Microsoft WinHeC 2004 presentation ddt301. Singularity performed much better on basic micro and macro benchmarks than we originally anticipated. savage. and when failing to perform well.. d. 9 (sept.).b. Hunt. J. limited to structs.r. The assumptions underlying generational collectors do not agree with the lifetime of many kernel objects that persist as long as the system or process exists. M. e.. Hodson. b. more than 30 interns contributed heart. July). In Proceedings of the 15th ACM Symposium on Operating Systems Principles (Copper Mountain resort. the inconsistencies between Sing#’s two type systems. solving the starting problem: device drivers as self-describing artifacts. and engler. Like any system. On today’s fast computers. springer. Finally. G.. In Proceedings of the EuroSys 2006 Conference (leuven. does not provide convenient mechanisms for manipulating bitlevel formatted data and inlined arrays found in device-control registers and network packets. s. extensibility.. Cook... belgium. M. In addition. Canada. Hunt. becker. acknowledgments Singularity was the work of large team of dedicated individuals: David Tarditi..r. P. This system allows static verification of channel contracts but exacts a price in programmer frustration and additional code for marshalling. ACM 51.. 47–58. J. Not adding this functionality to Sing# early in the Singularity-development project was an omission that continues to incur a penalty. Wa. 260–264. 2003. 2. J. Jakob Rehof. G. conclusion Singularity is a small operating system we and a group of our colleagues at Microsoft Research built to demonstrate a nontrivial change in the standard practice of designing and constructing software. In addition. Data in a process is conventional C# objects.. Fähndrich.). Sing#. 12. safe programming languages enable new system architectures that not only improve robustness but perform better in many circumstances than traditional approaches. G. new york. Wa. r. and hardware access.. aiken. Chou.. Steven Levi. Hinchey.. C#. Jacobs. Mar.codeplex. James Larus (larus@microsoft. Hunt.n. new orleans. problems were seldom attributable solely to garbage collection.G..... the netherlands. M. Manuel Fähndrich. levi. deline. o. safety and performance in the sPIn operating system. J. M. new york. unmarshalling. and operations on the structs. software isolation.00 AU g U ST 2 0 1 0 | VO l. banff. 4. la. sirer.. Hawblitzel. a. larus. Mark Plesko. 341–354. not objects. 73–88. boogie: a modular reusable verifier for object-oriented programs. and Richard Black built portions of the operating system. Increased interoperability or. belgium. barnett. our experience shows that high-performance system software can be built in a garbage-collected language. Hallem. 7. redmond. b... aCM Press. replacing in-process plug-ins with components in separate processes would improve the resilience of any system. and Margaria.. Gradually incorporating safe languages.. 9. s. new york. C. levi. Flatt. apr. 2006. new york. Orion Hodson. Galen hunt (galenh@microsoft. deconstructing process isolation. a unified type system would simplify the code for creating and manipulating messages. aCM Press. is common in conventional operating systems and deserves reexamination as a garbage-collection technique for safe kernels. d. Source code for the Singularity system is available for noncommercial use at. Fähndrich.. K. Commun. and leino. In Proceedings of the 18th ACM Symposium on Operating Systems Principles (Chateau lake louise. the channel contracts we used were not expressive enough to describe asynchronous interactions between processes. tarditi. b. Nick Murphy. 37–49. and tricker. and Tim Harris worked on Sing# and tools.. and C#’s incomplete type system. 10. Rebecca Isaacs. spear. V. Brian Zill. Hunt. cross-process communication. and increased specification into existing systems offers cost-effective incremental improvement. 2007. t. s. © 2010 aCM 0001-0782/10/0800 $10. Ted Wobber. Bjarne Steensgaard. 6. J. 2004. G.. M. 2006. 54–59. Portugal. yang. Songtao Xia. In Proceedings of the ACM SIGPLAN Workshop on Memory Systems Performance and Correctness (san Jose. o.. M. aiken.. Ulfar Erlingsson. and Hunt. the slaM toolkit. 1995. t. An Introduction to Driver Quality. Qunyan Mangus. like many modern languages.P. aCM Press.. Ed Nightingale.com/singularity. M.. b.). Jackson.. aCM Press. sealing os processes to improve dependability and safety. language support for fast and reliable message-based communication in singularity os. software engineering and formal methods.. Kill-safe synchronization abstractions. 1–10. s. and Chambers.F. Pardyak. Herman Venter. 5. d.e.r. Chelf. 364–387. In Proceedings of the 2004 ACM SIGPLAN Conference on Programming Language Design and Implementation (Washington. d. r. Fiuczynski. M. 267–284. 8. s. Change. ACM SIGOPS Operating Systems Review 41. 2001. C. but data passed along channels lives in a distinct type system. Singularity also has its rough spots. b. 3. Martin Abadi. Co. 2001. C.. Chris Hawblitzel. and Findler. 45–58. June).C. Reference counting. The design of an optimal garbage collector for an OS kernel is an open question. nov. bershad. steensgaard. C. G. oct.). The lessons of Singularity are applicable far beyond the ground-up design of new systems. 2006. Cousot. and larus. compiled runtime system for safe code. References 1. 11.). and larus.. Hawblitzel. Hodson. Singularity shows that modern. Hawblitzel. better. Ca. Andrew Birrell. aCM Press.. despite trade-offs involving cost and the inability to reclaim cyclic structures. it is no longer necessary to design systems around the lowest common denominator of assembly language or C. and Juan Chen built the Bartok compiler and runtime. singularity: rethinking the software stack. M. t.. the language of Singularity. In Proceedings of the Second ACM SIGOPS/EuroSys European Conference on Computer Systems (lisbon. aCM Press.. for example. apr. oct. Sriram Rajamani. Likewise.. new york.. supports two type systems: C# and data passed between processes.
  illustrating our approach with data collected from the portals Digg (. whereby content is submitted. Web hosts. and videos that draw millions of viewers are prominently displayed on the site. and leave comments. By GaBoR SzaBo anD BeRnaRDo a. blogs.0 services has transformed the landscape of online content consumption. two well-known examples of popular content-sharingand-filtering services. whereas a few receive the most attention. reply to them through their own videos. Digg is an example.com) and YouTube (. collaborative portals. Research shows that user attention9 is allocated in a rather asymmetric way. and discussed by the user community.” This placement results in a positive feedback mechanism leading to rich-get-richer vote accrual for the very popular items. it is notably difficult to predict the amount that will be devoted over time to any given item. anyone with Internet access can watch YouTube videos. While it is possible to predict the distribution of attention over many items. social bookmarking. though the pattern pertains to only a small fraction of the submissions that rise to the top. 5 3 | NO. The articles attracting the most votes are exhibited on the site’s premiere sections under headings like “recently popular submissions” and “most popular of the day. The way the online ecosystem has developed around YouTube videos is impressive by any standard. Content providers. Besides Digg. huBeRman Predicting the Popularity of online content producing online content highlights the problem of predicting how much attention any of it will ultimately receive. where the “wisdom of the crowd” provides collaborative filtering to select submissions favored by as many visitors as possible. With the Web.1787254 Early patterns of Digg diggs and YouTube views reflect long-term user interest. content producers can reach an audience in numbers inconceivable through conventional t h e e Ase oF 80 comm unicaTio nS o f Th e ac m | AU gU ST 201 0 | VO l . and news aggregators. and providers would all find it useful to be able to predict content popularity. Examples of services that have made the exchange between producer and consumer possible on a global scale include video. rated. Portals often rank and categorize content based on past popularity and user appeal. The ubiquity of Web 2. wikis. especially for aggregators. . and advertisers all would like to be able to predict how many views and downloads individual items might generate on a given Web site. photo. early patterns of access indicate longterm popularity of content. 8 channels.contributed articles Doi:10. For example in advertis- key insights Site administrators. with users submitting links to and short descriptions of content they have found on the Web and others voting on them if they find them interesting.com). We solve this problem here. Prediction is possible due to the extreme regularity with which user attention focuses on content. and music sharing. perused.1145/ 1787234. like stories on Digg. with most content getting only some views and downloads. advertisers.
  2008 (bottom) and all stories (close up) Dec. Based on data we collected from Digg in the second half of 2007. along with surrogates to the submission (a short description for news. Digg allows users to submit links to news. Submitted content is placed by the submitters on Digg in the so-called “upcoming” section.2% to videos. per Digg terminology. Fans are shown updates on which submissions are dugg by these users.7 thus modulating the influence of very popular submitters with hundreds of followers. Moreover. in content-distribution networks. 2008 (top) rendered as a series of tree-ring-like visualizations moving outward in time. 2007 to may 23. registered users thus digg submissions they find interesting. 81 VIsua lIZatIon by CHrIs H arrIson. Digging increases the digg count of the submission one digg at a time. since we were interested in submissions to which many users had access. and submissions that get enough diggs in a certain amount of time in the “upcoming” section are shown on the Digg front page. if popularity count is tied directly to ad revenue (such as with ads shown with YouTube videos). Digg functions as a massive collaborative filtering tool to select and share the most popular content in the user community.” Promotion is a considerable source of pride in the Digg community and a main motivator for repeat submitters. “promoted. 2004 to may 23. Here. or. the computational requirements for bandwidth-intensive new content may be determined early on if the hosting site is able to extrapolate the number of requests the content is likely to get by observing patterns of access from the moment it was first posted. 8 | c om m u n ic aT ion S of T he acm . we consider only stories that were promoted. CarneGIe Mellon unIVersIt y AU g U ST 2 0 1 0 | VO l. 9. images. revenue might fairly accurately be estimated ahead of time if all parties know how many views the video is likely to attract.5% of all uploads were links to news. ing. and only 0. and videos they find on the Web and think will interest the site’s general audience. Links to content are provided. a thumbnail image for images and videos) intended to entice readers to peruse the content. The exact algorithm for promotion is not made public to thwart gaming but is thought to give preference to upcoming submissions that accumulate diggs quickly from diverse neighborhoods in the Digg social network. the social network therefore plays a major role in making upcoming submissions more visible to a larger number of users.key Sports offbeat Sunday monday Tuesday Wednesday Thursday friday Saturday entertainment Gaming Science Lifestyle Technology World & Business chris harrison’s Digg Rings visualization plots the top 10 most-dugg stories by days of the week may 24. Digg’s social-networking feature lets users place watch lists on other users by becoming their fans. 90.3% to images. 1. 53 | N O. one click from the site’s main page.
  2008.3.” “most discussed. appearing as embedded objects on the referring page. Daily and weekly cycles in the hourly rates of digging activity. 2007 (Sunday). showing the average normalized popularity for all submissions over time. The number of submissions was about 1.com/apis/youtube/ overview. The inset is the same measurement for the first 48 digg hours of Digg submissions. we multiplied the rates for submissions by 10 and the rates of promotion by 1.” and “most viewed. Apart from the list of “most recently added” videos.4 0.2 1 0. with (as of 2008) 65.6 0. However.3 million. we obtained a time series of popularities that monotonically increased from 0 (at submission time) to 1 at day 30. videos might have been linked from external sources as well. respectively. This data set included approximately 29 million diggs by 560. digg. respectively. due to the fact that the view-count field of a video did not appear to have been updated more often than once a day by YouTube. only about 3% of the views came from these links. average normalized popularity of submissions to Digg and youTube by individual popularity at day 30. dividing their popularity values before that time by this final number. 2007 (monday)–august 12.2 Popularity Growth By “popularity” we mean number of votes (diggs) a story collected on Digg and number of views a video received on YouTube. carrying out data collection for the next 30 days. YouTube is the apex of the Web’s user-created video-sharing portals.” We chose the “most recently uploaded” list to give us an unbiased sample of all videos submitted to the site or complete history of the view counts for each video during its lifetime. digg youtube average normalized popularity 1.contributed articles We used the Digg application programming interface (. 8 . we averaged overall submissions of the normalized popularities.1%) were promoted to the front page.html)10 provided programmatic access to several video statistics. An important difference between the two portals is that while Digg stories saturate fairly quickly (about a day) to their respective reference populari- figure 1. diggs submissions * 10 promotions * 1.000 users on approximately 2. 2007 to December 18. and story promotions.000 14000 12000 count/hour 10000 8000 6000 4000 2000 0 Mon tues Wed thu Time Fri sat sun Mon 82 communicaT io nS o f T h e ac m | AU g U ST 201 0 | VO l . we first determined the popularity of each individual submission at the end of the 30th day following its submission. 2007. with view count at a given time being one of them.000. story submissions.000 (7. a number including all past submissions receiving any digg.2 0 0 10 20 30 40 Time (digg hours) figure 2.146 selected videos daily in the portal’s “recently added” section. YouTube’s API ( 0. we were able to calculate only a good approximation of the number of daily views.4 0.000 new videos uploaded and 100 million viewed daily. of which about 94. while another gets thousands or even millions). Pacific Standard Time.7 million submissions. To match the different scales. while 50% of all videos in 2007 were thought to be linked externally. By thus eliminating the prevailing differences in content-specific interestingness among the submissions (one submission might get only a few views over its lifetime. it also offered listings based on such YouTube-defined selection criteria as “featured.6 It was also the third most frequently accessed site on the Web. The horizontal axis represents the week august 6. based on traffic rank. 5 3 | NO.2 0 0 5 10 15 Time (days) 20 25 30 1 0.1 Beginning April 21. implying that 60% of all online videos were watched through YouTube. not only the submissions during the six months. Worth noting is that while the overwhelming majority of video views was initiated from the YouTube Web site itself. For each submission.google. Figure 1 reflects the dynamics of content popularity growth on both portals. we collected view-count time series on 7.8 0. The tick marks are midnight on the respective day.8 0.com/)4 to retrieve all diggs made by registered users from July 1.
  contributed articles
  ties, YouTube videos keep attracting views throughout their lifetimes. The rate videos attract views may naturally differ among videos, with the less-popular likely marking a slower pace over a longer time. These two notably different userpopularity patterns are a consequence of how users react to content on the two portals. On Digg, articles quickly become obsolete, since they often link to breaking news, fleeting Internet fads, or technology-related themes with a naturally limited time for user appeal. However, videos on YouTube are mostly found through search, since, with the sheer number of videos constantly being uploaded, it is not possible to match Digg’s way of giving each promoted story general exposure on a front page. The quicker initial rise of video view counts can be explained through the videos’ exposure in YouTube’s “recently added” section, but after leaving it, the only way to find them is through keyword search or when displayed as related videos next to another video being watched. The short fad-like popularity life cycle of Digg stories (a day or less) suggests that if overall user activity on Digg depends on time of day, a story’s popularity may grow more slowly when fewer visitors are on the site and increase more quickly at peak periods. For YouTube, this effect is less relevant, since video views are spread over more time, as in Figure 1. Figure 2 outlines the hourly rates of user digging, story submitting, and upcoming Digg story promotions as a function of time for one week, beginning August 6, 2007. The difference in rates may be as much as threefold; weekends showed less activity, and weekdays appeared to involve about 50% more activity than weekends. It was also reasonable to assume that besides daily and weekly cycles, such activity also involved seasonal variations. Moreover, in 2007, Digg users were mostly located in the UTC-5 to UTC-8 time zones (the Western hemisphere). Depending on the time of day a submission was made to the portal, stories differed greatly in the number of initial diggs they received. As we expected, stories submitted during less-active periods of the day accrued fewer digs in the first few hours than stories submitted during peak hours. This was a natural consequence of suppressed
  figure 3. correlation of digg counts on the 17,097 promoted stories in the data set older than 30 days. a k-means clustering separates 89% of the stories into an upper cluster; the other stories are a lighter shade of blue. The bold line indicates a linear fit with slope 1 on the upper cluster, with a prefactor of 5.92 (Pearson correlation coefficient of 0.90).
  104
  Popularity after 30 digg days
  103
  102
  101 101 102 Popularity after one digg hour 103
  figure 4. Popularity of videos on the 30th day after upload vs. popularity after seven days. The bold line with gradient 1 is fit to the data.
  105 Popularity after 30 days 104 103 102 101 100 100 101 102 103 104 105
  Popularity after seven days
  digging activity at night but might have initially penalized interesting stories that were otherwise likely to be popular. For instance, an average story promoted at 12 p.m. received approximately 400 diggs in the first two hours and only 200 diggs if promoted at 12 a.m. That is, based on observations made after only a few hours after a story was promoted, a portal could misinterpret the story’s relative interestingness if it did not correct for the variation in daily user-activity cycles. Since digging activity varies by time, we introduce the notion of digg time measured not in seconds but in number of diggs users cast on promoted sto-
  ries. We count diggs only on promoted stories because this section of the portal was our focus, and most diggs (72%) were to promoted stories anyway. The average number of diggs arriving at promoted stories during any hour day or night was 5,478 when calculated over the full six-month data-collection period; we define one digg-hour as the time it takes for so many new diggs to be cast. As discussed earlier, the time for this many diggs to arrive took about three times longer at night than during the day. This “detrending” allowed us to ignore the dependence of submission popularity on the time of day it was submitted. Thus, when we refer to
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  the. Predicting the future YouTube
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  While Digg stories saturate fairly quickly (about a day) to their respective reference popularities, youTube videos keep attracting views throughout their lifetimes. indepth) = ln r(ti, tr) + lnN(ti) + ξ(ti, tr), where N(t) is the popularity of a particular submission at time t; r(ti, tr) accounts for the linear relationship between the log-transformed popularities at different times; and ξ is a noise term (describing the randomness we observed in the data) that accounts for the natural variances in individual content dynamics beyond the expected trend in the model and is drawn from a fixed distribution with mean 0. It is important to note that the noise term is additive on the log-scale of popularities, justified by the fact that we found the strongest correlations on this
  | AU gU ST 201 0 | VO l . 5 3 | NO. 8
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  transformed scale. In light of Figures 3 and 4, the popularities at tr also appear to be evenly distributed around the linear fit, taking only the upper cluster in Figure 3 and considering the natural cutoff y = x in the data for YouTube. We also found that the noise term (given by the residuals after a linear fit in both the YouTube and the Digg data) is well described by a normal distribution on the logarithmic scale. However, there is also an alternative explanation for the observed correlations: If we let ti vary in the model just described we see that the popularity at the given time tr should be described by the following formula, assuming the noise term in the model is distributed normally (t0 is an early point in time after submission/promotion): lnN(tr) = lnN(t0) + ∑ η(τ).
  τ=t0 tr
  η(τ) is a random value drawn from an arbitrary, fixed distribution, and τ is taken in small, discrete timesteps. The argument for this process is as follows: If we add up a large number of independent random variables, each following the same given distribution, the sum will approximate a normal distribution, no matter how the individual random variables were distributed.5 This approximate normal distribution is the result of the central limit theorem of probability and why normal distributions are seen so often in nature, from the height of people to the velocity of components of atoms in a gas. If we consider the growth of submission popularity as a large number of random events increasing the logarithm of the popularity by a small, random amount, we arrive at the log-linear model just described. What follows from the model is that on the natural, linear scale of popularities we must multiply the actual popularity by a small, random amount to obtain the popularity for the next timestep. This process is called “growth with random multiplicative noise,” an unexpected characteristic of the dynamics of user-submitted content.9 While the increments at each timestep are random, their expectation value over many timesteps adds up, ultimately to ln r(t0, tr) in the log-linear model. Thus the innate differences among the user-perceived interesting-
  ness of submissions should be seen early on, up to a variability accounted for by the noise terms. Popularity prediction. To illustrate how a content provider might use the random logarithmic growth model of content popularity on Digg and YouTube, we performed straightforward extrapolations on the data we collected to predict future access rates. If submissions do not get more or less attractive over time as they were in the past, we expect their normalized popularity values to follow the trends in Figure 1. The strong correlation between early and later times suggests a submission that is popular at the beginning will also be popular later on. The linearity of popularity accrual with a random additive noise on the logarithmic scale also allows us to approximate the number of views/diggs at any given time in the future; they are predicted to be a constant product of the popularity measured at an earlier time. However, the multiplier depends on when the sampling and the prediction are performed. In order to perform and validate the predictions, we subdivided the submission time series data into a training set and a test set. For Digg, we took all stories submitted during the first half of the data-collection period (July to mid-September 2007) as the training set and the second half as the test set. On the other hand, the 7,146 YouTube videos we followed were submitted at about the same time, so we randomly selected 50% of them as training and the other 50% as test; the table here outlines the numbers of submissions in the two sets. The linear regression coefficients between ti and tr data were determined on the training set, then used to extrapolate on the test set. Content popularity counts are often related to other quantities, like click-through rates of linked adver-
  tisements and number of comments the content is expected to generate on the community site. For this reason we measured the performance of the predictions as the average relative squared error over the test set or as the expected difference of a prediction from the actual popularity, in percentages. For a reference time of tr to predict the popularity of submissions we chose 30 days after submission time. Since the predictions naturally depend on ti and how close we are to the reference time, we performed the parameter estimations in hourly intervals starting immediately after the introduction of a submission. The parameter values for the predictions (ln r(ti, tr) in the log-linear model discussed earlier) can be obtained with maximum likelihood fitting from the training-set data. The errors measured on the test set (see Figure 5) show that the expected error decreases rapidly for Digg (negligible after 12 hours), while for YouTube the predictions converge more slowly to the actual value. After five days, the expected error made in estimating the view count of an average video was about 20%, while the same error was attained an hour after a Digg submission. This is due to the fact that Digg stories have a much shorter life cycle than YouTube videos, and Digg submissions quickly collect many votes right after being promoted. The simple observation that the popularities of individual items are linearly related to each other at different times enables us to extrapolate to future popularities by measuring content popularity shortly after the content is introduced. However, the detailed parameter-estimation procedure strongly depends on the idiosyncrasies of the random multiplicative model and the type of error measure we wish to minimize (such as absolute and relative), so
  Partitioning the collected data into training and test sets, we divided the Digg data by time and chose the youTube videos randomly for each set, respectively.
  Training set Digg youTube 10,825 stories (7/1/07–9/18/07) 3,573 videos randomly selected
  Test set 6,272 stories (9/18/07–12/16/07) 3,573 videos randomly selected
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  respectively.1 0 0 5 10 15 20 Digg story age (digg hours) (a) 1 0.contributed articles figure 5. Digg’s approach to social networking is to make it possible for users to be fans of other users. Results are outlined in Figure 7. with about 400 new submissions an hour in 2007. most diggs are cast by users who could not have seen the submission in their social network before. these users are relatively dense in the neighborhood of the small social graph in Figure 6. the effect of the social network becomes negligible. this measurement is the probability that a new digg is made by users who may have seen the story through their social networks. This falloff in peer following supports the assumption that stories are found through the social network in the “upcoming” phase.2 0 0 5 10 15 20 25 30 youTube video age (days) (b) these constraints must be considered to achieve the minimum error possible allowed by the model. Users who dugg a particular story are in red. where a link represents whether a particular user is a fan of another user. 5 3 | NO. We normalized the times of diggs with respect to the promotion time of the individual submissions. with no apparent clustering among them. do diggers pay attention to what their idols already dugg? To see how Digg social networking functioned we took all submissions for which we had data for at least 12 hours after promotion and measured the fraction of diggers with at least one digger among their idols and who had already dugg the same story. we focus on the network of Digg users. Social networking Social networking features in Web 2. Prediction performance is based on the logarithmic growth model measured by the average relative squared error function for (a) Digg and (b) youTube. but users themselves select the peers they wish to follow. Together with content-popularity data. Due to the limited nature of social-networking options on YouTube in 2008. as in Figure 2. the null hypothesis for user Relative squared error | AU gU ST 201 0 | VO l . where recent diggs of a user’s idols are visible for more time on the user’s personal page. considerably more than the average submission at the time. Though all new submissions are shown in the “upcoming” section.0 services are so ubiquitous it is almost mandatory for a site to offer them to its users. Figure 6 shows a typical snapshot of the Digg social network in 2007. after which they are able to see what stories their “idols” submit or digg. The most effective way to discover new stories should thus be through the social network. but once they are promoted to the front page and exposed to a diverse audience for a longer time. While users are about three times more likely to digg a submission their idols dugg in the “upcoming” phase than after it was promoted. This is essentially a restricted form of collaborative filtering.6 0. For example. with new stories appearing at the top of the “upcoming” page on average every ninth second. the list is updated so quickly that entries left the first page in about two minutes. since the story attracted nearly 15.8 Relative squared error 0. It was known that the Digg social network plays an important role in making a story visible and popular when the submission is still in Digg’s “upcoming” section. we also collected link information using the Digg API. they might have seen if friends recently uploaded videos. The shaded areas indicate one standard deviation of the individual submission errors around the average. so for diggs made before promotion.5 0. However.3 0. To determine whether diggers are truly influenced by their social peers. 0. when it was still in the “upcoming” phase. In essence. however.4 0. However. the measurement only intuitively suggests that users pay attention to the activities of their peers. where about 20% of diggers have an idol who dugg the same story before they did. time is measured backward. this figure drops considerably (to 7%) after promotion. A similar kind of social network is active in YouTube.4 0. To what extent then. 8 .2 0. though the feature that allowed users to follow the videos their friends were watching was nascent in 86 communicaT io nS o f T h e acm 2008.000 diggs altogether. with about 260 users and 550 links.
  that is. However.15 0.contributed articles diggs would be a scenario in which users pick stories randomly. We simulated a scenario whereby users made their diggs at exactly the same times as they would in real time to mimic the sessions when they’re logged onto Digg. and most important. The controversy in this result might be resolved if we consider that once a submission is promoted to the front page (shortly after time 0 in the figure). rather than what users actually dugg. In Figure 7. they are unlikely to have an extended (or even any) social network. The vertical red line marks time 0 (promotion time). it matters figure 6. it gains tremendous visibility compared to the “upcoming” phase and is exposed to many casual Digg users. we performed the same measurement as in Figure 7 to determine how agents might have been influenced by their idols to digg the same stories as their idols. figure 7. users seem to do the opposite of their peers: The probability that a new digger is a fan of a previous digger of a story is significantly less than one would expect from random choice. never being influenced by what their idols did before them. though they do not digg often. 53 | N O. Consequently. If the observed fractions substantially exceed the random expectation. These users do not actively participate in discovering new submissions but browse the Digg main page to see what other users found interesting (making up the bulk of the user base). non-diggers are in green.1 0. we can safely say that users indeed pick the same submissions as their peers.2 0.25 fraction of new diggers who are fans of earlier ones 0. This approach ensured that the simulated agents picked a random story from among all the stories available to them. with the average calculated over all diggs on all stories. Time is relative to the promotion time of the story. we let the agents representing the users digg any story present in the system. right after promotion. 8 | c om m u n ic aT ion S of T he acm 87 . After the agents’ selections were randomly made. Measured random hypothesis 0. stories late in the “promoted” phase get diggs from users who do not watch their links at all. We maintained (important) the agents’ social links and corresponding user links. the difference between the random model (green line) and the observed digging pattern (blue line) is obvious: Users digging stories in the “upcoming” phase were more than twice as likely to digg what their idols dugg than they would if there was no social network—the same as picking a story randomly. At the same time. the observed probability of peer influence is diminished. Probability that a digger of a story is a fan of a digger who dugg the same story (blue line) as a function of the time of the digg. The beneficial effect of a social network on content popularity is therefore confined to less active periods of the content’s life cycle.05 0 –2 0 2 4 Popularity after seven days AU g U ST 2 0 1 0 | VO l. We randomly selected a user as origin and included every other user in the social graph with snowball sampling up to distance four from the user following breadth-first search. their compounded activity dominates the diggs a story gets at this stage. Diggers of a particular story are in red. However. However. the random hypothesis delivers the same fractions as the real observations after about a day. The green line is the same measurement but with diggs randomly shuffled. and negative times refer to the “upcoming” phase. We were able to test whether users digg stories according to the random null hypothesis by randomly shuffling their activities. so we could observe the presence or lack of a social-network effect. Representative example of a Digg-user social network. and.
  the social network provided by the service does not affect which users will tend to look at the content. it would be interesting to extend the analysis by focusing on different sections of the portals (such as how the YouTube “news & politics” section differs from the YouTube “entertainment” section). Predictions are therefore more accurate for submissions for which attention fades quickly. Based on our understanding of this correlation. On a technical level. J. In Proceedings of the Seventh ACM SIGCOMM Conference on Internet Measurement (san diego. 2007). while YouTube videos are still found long after they are submitted to the portal. 5. Kwak. Z.. In Proceedings of the 16th International Workshop on Quality of Service (enschede. aCM Press. 2008). dale. IEEE Internet Computing (Special Issue on Social Search) 11. © 2010 aCM 0001-0782/10/0800 $10. 4... 229–238. In Proceedings of the Seventh ACM SIGCOMM Conference on Internet Measurement (san diego. richardson. We would also like to learn whether it is possible to forecast a Digg submission’s popularity when the diggs come from only a small number of users whose voting history is known. new york. 6. Vol. 9. predictions can be based on observed early time series. while downloads of YouTube videos had to be followed for 10 days to achieve the same relative error. John Wiley & sons. e. 6 (nov.com) is a research scientist in the social Computing lab at Hewlett-Packard labs. 1968. ahn. An Introduction to Probability Theory and Its Applications. 2007. new york. F.alexa. Ca. r. as it is for stories in Digg’s “upcoming” section.8 In the presence of a large user base. while semantic analysis of content is more useful when no early click-through information is available. June 2–4. Wu. oct. and ragno. 1–14. a strong linear correlation exists between the logarithmically transformed popularity of content at early and later times. For example. M. this semantics of popularity may be used to predict click-through rates in the absence of early-access data.. everybody tubes: analyzing the world’s largest user-generated content video system. In Proceedings of the 16th International Conference on the World Wide Web (banff.. 15–28. and Huberman. P. 1. and social networks are thus not effective promoting downloads on a large scale.-y. social information processing in news aggregation. We performed experiments showing that once content is exposed to a wide audience. a. new york. Gill. x. 2007. aCM Press.html Gabor Szabo (gabors@hp. Predicting clicks: estimating the click-through rate for new ads.huberman@hp. Cheng. Digg stories quickly become outdated. and liu. novelty and collective attention. Inc. arlitt.. Proceedings of the National Academy of Sciences 104. they are important in the stages when content exposure is constrained to a small number of users.contributed articles only when its visibility is minuscule compared to its other stages. 5 3 | NO. 7. 3. May 8–12). 8.com/apis/youtube/ overview. and Mahanti. Feller. P. 88 com municaTio nS o f T h e ac m in the presence of a large user base. I tube. K. However. we presented a model to be used to predict future popularity... 45 (nov. and the highest number of diggs accrues when the social-network effect is nonexistent. alexa Web Information service. we could not explore several related areas here. We thus based our predictions of future popularity only on values measurable at the time we did the study and did not consider the semantics of popularity and why some submissions become more popular than others. oct. you tube. li. new york. M. 10. rodriguez. C. References 1. 521–530. Palo alto. Bernardo A. We therefore do not consider this feature (otherwise deemed important) a main contributor from a prediction point of view in terms of total popularity count. huberman (bernardo.com 2. Ca. lerman.00 | AU g U ST 201 0 | VO l . 8 . Cha.. 16–28. predictions can be based on observed early time series. youtube traffic characterization: a view from the edge. and Moon. youtube aPI. the netherlands. b.. Canada. measuring access to given stories during the first two hours after posting allowed us to forecast their popularity 30 days ahead with a remarkable relative error of 10%. 2007. 24–26). M. comparing its performance to the data we collected. whereas predictions for content with a longer life cycle are prone to larger statistical error. However. however. 24–26)... The differing time scales of the predictions are due to differences in how content is consumed on the two portals.a.. dominowska. In Digg. conclusion In this article we have presented our method for predicting the long-term popularity of online content based on early measurements of user access. W. with the residual noise on this transformed scale being normally distributed. 2007). aCM Press. H. Palo alto.google. y. while semantic analysis of content is more useful when no early clickthrough information is available. alberta. statistics and social network of youtube videos. digg aPI. Using two very popular content-sharing portals—Digg and YouTube—we showed that by modeling the accrual of votes on and views of content offered by these services we are able to predict the dynamics of individual submissions from initial data.com) is an HP senior Fellow and director of the social Computing lab at Hewlett-Packard labs.. s.
  2010 to qualify for consideration. from any country. Financial sponsorship of the award is provided by Google. and quality of presentation. Submissions Nominations are limited to one per university or college.org.D. eligibility Each nominated dissertation must have been accepted by the department between October 2009 and September 2010.eng@acm. (Copyright reverts to author if not selected for publication. Selection Procedure Dissertations will be reviewed for technical depth and significance of the research contribution. for Submission Procedure See. in which case two may be nominated. Please send a copy of the thesis in PDF format to emily. These awards are presented annually at the ACM Awards Banquet.Call for Nominations The ACM Doctoral Dissertation Competition Rules of the competition ACM established the Doctoral Dissertation Award program to recognize and encourage superior research and writing by doctoral candidates in computer science and engineering. followed by an in-depth evaluation to determine the winning dissertation.000. A one-page summary of the significance of the dissertation written by the advisor must accompany the transmittal.cfm .000 and the Honorable Mention Award is accompanied by a prize of $10. Deadline Submissions must be received at ACM headquarters by october 31. unless more than 10 Ph. award The Doctoral Dissertation Award is accompanied by a prize of $20.) Publication Winning dissertations will be published by Springer.acm. potential impact on theory and practice.’s are granted in one year. A committee of five individuals serving staggered five-year terms performs an initial screening to generate a short list. The selection committee will select the winning dissertation in early 2011.org/html/dda. Publication Rights Each nomination must be accompanied by an assignment to ACM by the author of exclusive publication rights. Sponsorship Each nomination shall be forwarded by the thesis advisor and must include the endorsement of the department head. Only English language versions will be accepted.
  aDVe anD hanS-J. The ability to pass memory references among threads makes it easier to share complex data structures. by implicitly sharing read-mostly data without the space overhead of complete replication. By SaRiTa V. largely because they are also useful for other purposes. 5 3 | NO. IllusratIon by G Wen Va nH ee . Threads were already widely supported by mainstream operating systems well before the dominance of multicore. for example. Although there is no consensus on parallel programming models. there are a number of reasons why threads remain popular. Finally.1145/ 1787234. 8 most pARALLeL pRogRAms today are written using threads potentially provides a performance advantage.1787255 Solving the memory model problem will require an ambitious and cross-disciplinary research direction. Boehm memory models: a case for Rethinking Parallel Languages and hardware and shared variables. Direct hardware support for shared-memory 90 communicaT io nS o f T h e ac m | AU g U ST 201 0 | VO l .review articles Doi:10. shared-memory makes it far easier to selectively parallelize application hot spots without complete redesign of data structures.
  byte code. Since 91 AU g U ST 2 0 1 0 | VO l. An overly constraining one may limit hardware and compiler optimization. or machine language) or any part of the language implementation (including hardware) without an unambiguous memory model. It defines the set of values that a read in a program is allowed to return. or any dynamic optimizer). is at the heart of the concurrency semantics of a sharedmemory program or system. or memory consistency model. It is not possible to meaningfully reason about either a pro- gram (written in a high-level. A complex memory model makes parallel programs difficult to write.art o evel in D ent pm The memory model. 53 | N O. the virtual machine. assembly. 8 | c om m u n ic aT ion S of T he acm . and parallel programming difficult to teach.. severely reducing performance. the compiler.
  each of these interleavings is a total order over all the steps performed by all the threads. software engineering. Figure 2 gives three possible executions that together illustrate all possible | AU gU ST 201 0 | VO l . and the implications for future research. Since 2000. languages. Before 2000. a strong hardware model is not very useful to programmers using languages and compilers that provide only a weak guarantee. For practitioners and educators. In the late 1980s and 1990s. informal. It was unclear what programmers expected hardware to do. or program order). and hardware. Whenever an object (that is. after much prior confusion. environments that addressed the issue with relative clarity. At the same time. or array element) is accessed.review articles it is an interface property. we outline an ambitious. and interleaving them in some way. formal methods.9. we had to address issues created by hardware that had evolved without the benefit of a clear programming model. This is partly because formally specifying a model that balances all desirable properties of programmability. Nonetheless. machine-specific descriptions proved mostly adequate in an era where parallel programming was the domain of experts and achieving the highest possible performance trumped programmability or portability arguments. and were difficult to teach. the execution can be viewed as taking all the steps executed by each thread. it is difficult to teach multithreaded programming without clarity on memory models. but are necessary for concurrency safety and debuggability. and then performing the next step in that thread’s execution (as dictated by the thread’s program text. consistent with the program order of each thread. hardware. there were a few programming 92 comm unicaTio nS o f Th e ac m key insights memory models. it has exposed fundamental shortcomings in our parallel languages and their interplay with hardware. and co-designed hardware that exploits and supports such semantics. This process has exposed fundamental shortcomings in our languages and a hardware-software mismatch. and environments as a whole. the area received attention primarily in the hardware community. and a new compiler release with a weaker memory model may require rewriting source code. first for Java and then C++. it is still unacceptably difficult to describe what value a load can return without compromising modern safety guarantees or implementation methodologies. Each access to a shared variable “sees” the last prior value stored to that variable in the interleaving. they were often violated to obtain sufficient performance. We call upon software and hardware communities to develop languages and systems that enforce data-race-freedom. it is still sometimes relegated to the “systems programming” section of the architecture manual. Semantics for programs that contain data races seem fundamentally difficult. Although this convergence is a dramatic improvement over the past. these languages and most hardware vendors have published (or plan to publish) compatible memory model specifications. Today. For researchers. This process is repeated until the program as a whole terminates. which describe the semantics of shared variables. A processor vendor cannot guarantee a strong hardware model if the memory system designer provides a weaker model. including cases of complete omission of the topic and some reflecting vendors’ reluctance to make commitments with unclear future implications. The program can be executed by interleaving the steps from the two threads in many ways. with little consensus. we have been involved in efforts to cleanly specify programminglanguage-level memory models. To us.32 Even when specifications were relatively clear. Formally. Finally. Thus.2 Commercial hardware memory model descriptions varied greatly in precision. In the process. a hardware architecture committed to a strong memory model cannot later forsake it for a weaker model without breaking binary compatibility. the central role of the memory model has often been downplayed. Part of the challenge for hardware architects was the lack of clear memory models at the programming language level. runtime systems. which explored many approaches. affecting portability and maintainability of programs. This often made it difficult to reconcile the need for a simple and usable programming model with that for adequate performance on existing hardware. and portability has proven surprisingly complex. Although the memory model affects the meaning of every load instruction in every multithreaded application. with efforts now under way to adopt similar models for C and other languages. For example. applications. This article discusses the path that led to the current convergence in memory models. this experience has made it clear that solving the memory model problem will require a significantly new and crossdisciplinary research direction for parallel computing languages. cross-disciplinary agenda toward resolving a fundamental problem in parallel computing today— what value can a shared variable have and how to implement it? Sequential consistency A natural view of the execution of a multithreaded program operating on shared variables is as follows. the memory model decision has a long-lasting impact. compilers. Each step in the execution consists of choosing one of the threads to execute. memory-model-related decisions for a single component must consider implications for the rest of the system.3 widespread adoption required consensus from the software community. the last value stored to the object by this interleaved sequence is retrieved. virtual machines. variable. are crucial to both correct multithreaded applications and the entire underlying implementation stack. which gives the core of Dekker’s mutual exclusion algorithm. the fundamental shortcomings it exposed.9 tended to be misunderstood even by experts. 8 .40 but the most widely used environments had unclear and questionable specifications. After decades of research. Although hardware researchers proposed approaches to bridge this gap. The central role of the memory model in parallel computing makes this article relevant to many computer science subdisciplines. including algorithms. performance. major programming languages are converging on a model that guarantees simple interleaving-based semantics for “data-race-free” programs and most hardware vendors have committed to support this model. 5 3 | NO. Effectively. consider Figure 1. we provide a succinct summary of the state of the art of this often-ignored and poorly understood topic. field.
  such as locks. and guarantee sequential consistency only if no undesirable concurrent accesses are present. There is also much work on speculatively performing these optimizations in hardware. // r1 == 0 // r2 == 1 execution 2 Y = 1. register promotion. We can make this more precise as follows. given non-sequentially consistent compilers). any execution must start with the first statement of one of the two threads. but do affect multithreaded programs (for example. r2 = X.536 if the assignment of 60. we avoid the above issues. r1 = Y. Sequential consistency gives us the simplest possible meaning for shared variables. data races). can r1 = r2 = 0? initially X=y=0 Red Thread X = 1. since we would have to forego them everywhere. core of Dekker’s algorithm. r1 = Y. this implies the meaning of even simple library operations depends on the granularity at which the library carries out those operations. Following Lamport. a compiler might. Programming languages generally already provide synchronization mechanisms. and sequential consistency does not prevent common sources of concurrency bugs arising from simultaneous access to the same shared data (for example.21). Since these operations occur adjacently in the interleaving. a program-ordered interleaving of operations of the individual threads) in which two conflicting ordinary operations execute “simultaneously. there are no intervening operations to enforce the order. it is not possible that both r1 and r2 are 0 at the end of an execution. In addition.000. Some executions for figure 1. In this case. execution 1 X = 1. and should be avoided. for example. For example. or at least explicitly highlighted. and at least one is a write. Consider two threads concurrently assigning values of 100. modern processors almost always use a store buffer to avoid waiting for stores to complete. aggressive speculation support). with rollback on detection of an actual sequential consistency violation (for example. reorder the two independent assignments in the red thread. programmers do not reason about correctness of parallel code in terms of interleavings of individual memory accesses. More generally. ˲˲ These transformations are detectable only by code that allows two threads to access the same data simultaneously in conflicting ways. Although many other interleavings are also possible. r2 = X. Ceze et al. for limiting simultaneous access to variables by different threads. Data-Race-free We can avoid both of the problems mentioned here by observing that: ˲˲ The problematic transformations (for example. Compilers. a very lowlevel notion.000 and 60. We assume the language allows distinguishing between synchronization and ordinary (non-synchronization or data) operations (see below). First. one thread must release a lock after accessing a shared variable.2 There is some work on compiler analysis to determine when such transformations are unsafe (for example. r2 = X. 8 | c om m u n ic aT ion S of T he acm 93 . these ideas are tied to specific implementation techniques (for example. We say that two memory operations conflict if they access the same memory location (for example. it only makes sense to reason about interleaving steps if we know what those steps are. such simultaneous accesses can remain dangerous. and hence may result in a non-sequentially consistent execution. making it expensive to forego the optimizations. reordering any pair of accesses. and vendors have generally been unwilling to commit to those for the long term (especially.000 to the shared variable X on a machine that accesses memory 16 bits at a time. However. r2 = X. The final value of X in a “sequentially consistent” execution may be 125.” For our purposes. reordering accesses to unrelated variables in Figure 1) never change the meaning of single-threaded programs. // r1 == 1 // r2 == 1 AU g U ST 2 0 1 0 | VO l. they are typically individual memory accesses. by allowing both r1 and r2 to be 0 in Figure 1). Thus. reading values from write buffers.review articles final values of the non-shared variables r1 and r2. redundant read elimination. also effectively reordering instructions in each thread. figure 2. one thread writes the data and another reads it. sequential consistency can be expensive to implement. We say that a program (on a particular input) allows a data race if it has a sequentially consistent execution (that is. it is not sufficiently simple and a much less useful programming model than commonly imagined. For example. Even with sequential consistency. Both the compiler and hardware optimization make an outcome of r1 == 0 and r2 == 0 possible. variable or array element). For Figure 1. Y = 1. for example. often have little information about sharing between threads. and figure 1. r1 = Y. // r1 == 1 // r2 == 0 execution 3 X = 1.000 occurred between the bottom and top half of the assignment of 100. To ensure that two conflicting ordinary operations do not happen simultaneously. Second. but suffers from several related flaws. and the variable assigned there will later be read as one. while sequential consistency may seem to be the simplest model. r1 = Y. Y = 1. most hardware and compilers today do not provide sequential consistency. they must be ordered by intervening synchronization operations. common subexpression elimination.26 an execution that can be understood as such an interleaving is referred to as sequentially consistent. Overall. Relying on sequential consistency without such highlighting both obscures the code. however. X = 1. or possibly transactional memory. 53 | N O. If we require that these be used correctly. and greatly complicates the implementation’s job. Blue Thread Y = 1. At a somewhat higher level. and many other hardware and compiler optimizations commonly used in uniprocessors can potentially violate sequential consistency. we know that they could equally well have occurred in the opposite order. Shasha and Snir37). since scheduling loads early tends to hide the load latency. two operations execute “simultaneously” if they occur next to each other in the interleaving and correspond to different threads.14 and Gharachorloo et al.
  r4 = X. albeit often through ad hoc techniques. except for the case of a write followed by a read. such as. Such models additionally provide fence instructions to enable programmers to explicitly impose orderings that are otherwise not guaranteed. Sparc’s TSO guarantees that a thread’s memory accesses will become visible to other threads in program order.1. The restriction on data races is not onerous. Conflicting accesses to such variables may occur simultaneously—since they are explicitly identified as synchronization (vs. the model does not provide any guarantees. Although data-race-free was formally proposed in 1990. These definitions are essentially equivalent. core 3 r1 = X. it is usually overkill to require that two program-ordered accesses always become visible to all threads in the same order or a write appears atomic to all threads regardless of the synchronization among the threads.1. on branches and addresses) which can result in subtle and complex interactions with data and control dependences.11) Data-race-free does not give the implementation a blanket license to perform single-threaded program optimizations. Some hardware implementations attempt to exploit this insight. Such a program-orderings + fences style of specification is simple. In addition to locks for avoiding data races. the full TSO specification. Thus. r3 =1.1. it is sufficient to preserve ordering and atomicity only among mutually synchronizing threads.12 A program that does not allow a data race is said to be data-race-free. hardware may make writes visible to different threads at different times through write buffers and shared caches. which incorporates one of the simplest atomicity optimizations. Second. r2 = 0.1. modern programming languages generally also provide a mechanism. PowerPC implements more aggressive forms of the optimization. core 2 Y = 1.9 but should not be. a thread usually relies on synchronization interactions to reason about the ordering or visibility of memory accesses on other threads. such as Java’s volatile variables. modern processors perform various forms of speculation (for example. To write Figure 1 correctly under data-race-free. Incorporating such optimizations increases the complexity of the memory model specification. Most hardware supports relaxed models that are weaker than sequential consistency. in well-written software. core 4 r3 = Y. we need simply identify the shared variables X and Y as synchronization variables. For example. generally remain illegal. this style implies that a write is an atomic or indivisible operation that becomes visible to all threads at once. where the desirable hardware optimizations drive the model specification. Third.20 Typical driving optimizations relax the program order requirement of sequential consistency. This would require the implementation to do whatever is necessary to ensure sequential consistency. but many subtleties make it inadequate. for example. industry Practice and evolution Hardware memory models.29 figure 3. TSO programmers may insert a fence between a thread’s write and read to ensure the execution preserves that order. synchronization-free sections of the code appear to execute atomically and the requirement to explicitly identify concurrent accesses makes it easier for humans and compilers to understand the code. As Figure 3 illustrates.2. The two writes generate invalidations for these caches. initially X = y = 0 core 1 X = 1. fence. recent updates now clarify the intent. Instead.2 First. giving the result shown and a deduction that X’s update occurs both before and after Y’s. if a 32-bit integer is used for synchronization purposes. they do not create a data race. We next describe the evolution of industry models to a convergent path centered around data-race-free. r4 = 0. It would also obligate the implementation to ensure that these synchronization accesses are performed indivisibly. it should not be visibly accessed as two 16-bit halves. with a specification that is complex and difficult to interpret even for experts. fence.review articles the other thread must acquire the lock before its access. The data-race-free model guarantees sequential consistency only for data-race-free programs. Further. as illustrated in Figure 4.1. the emergent shortcomings of data-race-free. where x might not otherwise have been written. thereby further complicating the memory model. and their implications for the future. These are commonly performed in certain contexts. Thus. ordinary). These could reach the caches in a different order.3 it did not see widespread adoption as a formal model in industry until recently. introducing the assignment x = x. 8 . in spite of those simultaneous accesses. (For more detail. violating write atomicity? 94 comm unicaTio nS o f Th e ac m | AU gU ST 201 0 | VO l . r2 = Y. Thus. for declaring that certain variables or fields are to be used for synchronization between threads. These models take an implementationor performance-centric view. it is also possible to define data races as conflicting accesses not ordered by synchronization. Assume a fence imposes program order. optimizations that amount to copying a shared variable to itself. This “sequential consistency for data-race-free programs” approach alleviates the problems discussed with pure sequential consistency. as is done in Java. The x86 documentation from both AMD and Intel was ambiguous on this issue. Most important hardware and compiler optimizations continue to be allowed for ordinary accesses—care must be taken primarily at the explicitly identified (infrequent) synchronization accesses since these are the only ones through which such optimizations and granularity considerations affect program outcome. but remain informal. is much more involved than the simple description here. 5 3 | NO.3 For programs that allow data races. In particular. hardware may not execute atomic or indivisible writes. see our technical report. however. Can r1 = 1. Assume core 3’s and core 4’s caches have X and Y.
  33 The effort was coordinated through an open mailing list that attracted a variety of participants. Nevertheless. it did not fully formalize the notion of well-synchronized and left uncertain the behavior of such programs. with widely varying interpretations even among experts participating in standards committee discussions. Such a scenario appears to violate any reasonable causality expectation and no current processor produces it. As we discuss later.review articles Incorporating these considerations in a precise way adds another source of complexity to program-order + fence style specifications. security. and/ or ambiguous enough to be misinterpreted even by experts. Java provided first-class support for threads with a chapter specifically devoted to its memory model.9 Without a real definition of the programming language in the context of threads. It was quickly decided that the Java memory model must provide sequential consistency for data-race-free programs. and/or ambiguous enough to be misinterpreted even by experts. Specifically. Unfortunately. 42) since this could clearly compromise safety and security. Java must support untrusted code running as part of a trusted application and hence must limit damage done by a data race in the untrusted code. excessively complex. for example. until the introduction of Java. the notions of safety. Ada was perhaps the first widely used high-level programming language to provide first-class support for shared-memory parallel programming. Prohibiting such causality violations in a way that does not also prohibit other desired optimizations turned out to be surprisingly difficult. but is allowed by the 95 hardware memory model specifications have often been incomplete. Although Ada’s approach to thread synchronization was initially quite different from both that of the earlier Mesa design and most later language designs. excessively complex. the Posix threads specification indicates a model similar to data-race-free. AU g U ST 2 0 1 0 | VO l. mainstream programming languages did not provide first-class support for threads. Pugh showed that this model was difficult to interpret and badly broken—common compiler optimizations were prohibited and in many cases the model gave ambiguous or unexpected behavior. High-level language memory models. data-race-free is inadequate for Java. although there are several inconsistent aspects. and “limited damage” in a multithreaded context were not clearly defined. representing hardware and software and researchers and practitioners. Sun appointed an expert group to revise the model through the Java community process. resulting in incorrect code or unnecessary loss in performance. Subsequently. Java cannot allow its reads to return values out-of-thin-air (for example.40 It used a style similar to data-race-free. make it impossible to guarantee that similar untrusted code cannot return a password that it should not have access to. Nevertheless. and hence what the programmer is allowed to assume. Further. the memory model must formally prohibit such behavior so that future speculative processors also avoid it. Figure 5 illustrates an example that also appears to violate causality. Since Java is meant to be a safe and secure language.32 In 2000. precise formalization of data and control dependences is a fundamental obstacle to providing clean high-level memory model specifications today. as discussed later. Previous work describes why the approach of an add-on threads library is not entirely satisfactory. they have often not been well-matched to software requirements. However. requiring legal programs to be well-synchronized. hardware memory model specifications have often been incomplete. 53 | N O. with related shortcomings. In summary. Figure 4(b) illustrates these issues. however. and shared-memory programming was mostly enabled through libraries and APIs such as Posix threads and OpenMP. It would. 8 | c om m u n ic aT ion S of T he acm . it is unclear what compiler transformations are legal. it was remarkably advanced in its treatment of memory semantics. The program has a data race and is buggy. The OpenMP model is also unclear and largely based on a flush instruction that is analogous to fence instructions in hardware models. The Java memory model. since hardware models have largely been driven by hardware optimizations. However. The challenge with defining the Java model was to formalize these notions in a way that minimally affected system flexibility. where volatile accesses (and locks from synchronized methods and monitors) were deemed synchronization. it cannot allow arbitrary behavior for data races.
  For thread 1. First. Core 1 may speculate X is 42 (for example. thread inlining is generally illegal under the Java model (even if there are no synchronizationand deadlock-related considerations). some optimizations that were intended to be allowed by the Java model are in fact prohibited by the current specification. This allows deducing that r1==r2 is always true.26 for a full description. increasing synchronization in the Java model can actually result in new behaviors. X = r2. Core 2 similarly writes X. Unfortunately. Thus. however. Redundant read elimination must be allowed. if (r1 == r2) Y = 1. after compiler transformation Thread 2 r3 = Y. More generally. Y = r1. no control dependences are violated since the speculation appears correct. initially X=y=0 original code Thread 1 r1 = X. A key reason for the complexity in the Java model is that it is not operational—an access in the future can determine whether the current access is legal. Further. however. if (r1 == 1) Y = 1. and the to-be committed write is not dependent on a read that returns its value from a data race. and the definition of well-behaved is the key source of complexity. The examples differ in that for the speculative write in the latter (Y=1). Certainly the current specification is much improved over the original. both reads now return 1. Then the compiler may move the write to before the read of X since no dependence is violated. was known to have some surprising behaviors. and that all these properties have more serious implications than previously thought. 5 3 | NO. the compiler could eliminate the redundant read of X. r2 = X. X = r3. but not that of Figure 4(b). then the inlined code can produce more behaviors than the original. many possible future executions must be examined to determine this legality. These conditions ensure that a future data race will never be used to justify a speculative write that could then later justify that future data race. the situation is still far from satisfactory. the current model was approved as the best compromise. and has recently been shown to have a bug. if (true). The behavior. core 2 r2 = Y. It is feasible for core 1 to speculate that its read of X will see 1 and speculatively write Y. be allowed if compilers are to perform the common optimization of redundant read elimination. for similar reasons. however. This outcome for the original code appears to violate causality since it seems to require a self-justifying speculative write of Y. the current specifi- | AU gU ST 201 0 | VO l . Committing a write early (before its turn in program order) requires it to occur in a wellbehaved execution where (informally) the already committed accesses have similar synchronization and data race relationships in all previously used well- behaved executions. The choice of future (well-behaved) executions also gives some surprising results. clearly. as discussed in Manson29 if the code of one thread is “inlined” in (concatenated with) another thread. even though more synchronization conventionally constrains possible executions. a read in a well-behaved execution has more choices to return values than before (since there are fewer data races). X = r3. creating a “self-fulfilling” speculation or a “causality loop. no processor today behaves this way. with other implications—it occurs because some data races in the original code may no longer be data races in the inlined code.36 In particular. Common to both Figure 4(b) and Figure 5 are writes that are executed earlier than they would be with sequential consistency. This notion of whether a speculative write could occur in some well-behaved execution is the basis of causality in the Java model. there is no sequentially consistent execution where Y=42 could occur. Is r1 = r2 = 42 allowed? (b) figure 5. Thread 2 r3 = Y. Fortunately. Recently. Part (b) shows an analogous causal loop with data dependences. Is r1 = r2 = 1 allowed? (a) initially X=y=0 core 1 r1 = X. it has been shown that. The Java model tests for the legality of an execution by “committing” one or more of its memory accesses at a time—legality requires all accesses to commit (in any order).29 After many proposals and five years of spirited debate. r1 = X. is nonintuitive. adding seemingly irrelevant reads or removing redundant reads sometimes can also add new behaviors. For Figure 4(b). It must. there is some sequentially consistent execution where it is exe96 comm unicaTio nS o f T he ac m cuted (the execution where both reads of X return 0). This model allows the outcome of Figure 5. thereby proving the speculation right and creating a causal loop that generates a value (42) out-of-thin-air. resulting in new behaviors. if (Y == 1) X = 1. 8 . We provide intuition for the model below and refer the reader to Manson et al. the prohibited optimizations are difficult to implement and this is not a significant performance limitation. making the write of Y unconditional.” Within a single core. It is unclear if current hardware or JVMs implement the problematic optimizations noted here and therefore violate the current Java model. Thread 1 Y = 1. this model is very complex. most programmers will not expect such an outcome (the code is in fact data-race-free since no sequentially consistent execution contains a data race). Is r1 = r2 = r3 = 1 allowed? common compiler optimization of redundant read elimination. In particular. In practice. r2 = r1. Subtleties with (a) control and (b) data dependences. Sequential consistency would allow both the reads of X and Y to return 1 in the new but not the original code. using value prediction based on previous store values) and (speculatively) write 42 into Y. Core 2 reads this and writes 42 into X. core 2 r2 = Y. initially X=y=0 core 1 r1 = X.review articles figure 4. Regardless. replacing r2=X with r2=r1. but the memory model specification needs to reflect this property. This means that when determining whether to commit a write early.
  Instead. As with the Java model. it affects a small number of fairly esoteric library calls. Earlier work10 points out.review articles cation does not meet its desired intent of having certain common optimizing transformations preserve program meaning. it clearly identifies shortcomings of existing compilers that we can now begin to remedy. (They require an explicit memory_order_ argument. (Correct answer: No.) Motivated by these observations. notably x86. is that a data race? (No. Since C++ does not support sandboxed code execution. Largely as a result. As we point out in Boehm and Adve12 this has a number of (mostly) performancerelated advantages. left significant uncertainties about the rules governing shared variables. It defines precisely what constitutes a data race. The situation in C++ was significantly different from Java. but portable. it is an important step forward. ˲˲ On some architectures. It is always possible to implement such synchronization variables by mapping each one to a lock. nearly all accesses simply read the atomic/ volatile flag and avoid lock acquisitions. not all memory accesses.a and x. we began an effort in 2005 to develop a proper memory model for C++. effectively making it erroneous to write such programs. even the fully fenced implementation may not be sequentially consistent. made it difficult to teach parallel programming since even the experts were unable to agree on some of the basic rules. Reconciling language and hardware models.) This resulted in a compromise memory model that supports data-race-free for nearly all of the language. Unfortunately the relevant specifications. it repeatedly became clear that current hardware models and supporting fence instructions are often at best a marginal match for programming language memory models. The Java model was largely guided by an emergent set of test cases. they were already in widespread use. The low-level operations are easily identified and can be easily avoided by non-expert programmers. even in the absence of data races. Second.33 based on informal code transformations that were or were not deemed desirable. We do not feel these were successful. Throughout this process. its inherent complexity and the new observations make it difficult to prove the correctness of any real system. such as pthreads22 or the corresponding Microsoft Windows facilities. (In light of modern (2009) specifications. However. and better reflects existing compiler implementations. and limited largely to atomic (C++) or volatile (Java) store operations. exactly the same issues arise if we rewrite Figure 4(b) with C++ atomic variables and use lowlevel memory_order_relaxed operations. It is part of the current Committee Draft24 for the next C++ revision. it seems undesirable that our specification of multithreaded program behavior would rest on such a complex and fragile foundation. we feel that although this solution involves compromises. the C++ draft standard can and does leave the semantics of a program with data races completely undefined. the cost on others. unless they are part of the same contiguous sequence of bit-fields. synchronization code that approaches the performance of assembly code. particularly since the lock accesses are likely to result in coherence cache misses. While it may be possible to fix the Java model. such as whether Figure 4(a) constitutes a data race. particularly in the presence of Java volatile fields or C++ atomic objects. 53 | N O. It clearly establishes data-race-free as the core guarantee that every programmer should understand. even when only read accesses are involved. and acquiring and releasing the corresponding lock around all accesses. this typically adds an overhead of hundreds of cycles to each access. that even thread library implementors often get confused when it comes to dealing explicitly with memory ordering issues. However. the section entitled “Implications for Languages” advocates a fundamental rethinking of our approach. but as inelegant as the Java one. with very similar atomic operations. and the threads API itself. 8 | c om m u n ic aT ion S of T he acm . both of which we still believe to be correct given existing hardware: ˲˲ A programming language model weaker than data-race-free is probably unusable by a large fraction of the programming community.b are assigned simultaneously. is modest.9 This made it unclear to compiler writers precisely what they needed to implement. resulted in very occasional failures for which it was difficult to assign blame to any specific piece of the implementation and. analogous to Java volatile) operations.) By doing so. The resulting effort eventually expanded to include the definition of atomic (synchronization. typically with the addition of a librarybased threads implementation. Substantial effort was invested in attempts to develop weaker. On hardware that relaxes write atomicity (see Figure 3). In addition to the issues raised in the “Lessons Learned” section.) But they do give expert programmers a way to write very carefully crafted. Since the initialization has to happen only once. A typical use is a flag that indicates a read-only data structure has been lazily initialized. It finally resolves simple questions such as: If x. but comparably simple and usable models. Unlike Java. atomic data types also provide low-level operations with explicit memory ordering constraints that blatantly violate sequential consistency. data-race-free involves substantial implementation cost. Nonetheless. The C++ memory model. Volatile and atomic variables are typically used to avoid locks for exactly these reasons. for example the combination of the C or C++ standard with the Posix standard. This development took place in the face of increasing doubt that a Java-like memory model relying on sequential consistency for data-race-free programs was efficiently implementable on mainstream architectures. for example. Our current solution to this problem is simpler. however. at least given the specifications available at the time. the specification methodology is inherently fragile— small changes usually result in hard-todetect unintended consequences. notably on some PowerPC implementations. it should be noted that this really only pushes Java’s issues with causality into a much smaller and darker corner of the specification. Even 97 AU g U ST 2 0 1 0 | VO l. Acquiring a lock to access the flag defeats the purpose. it is often unclear that more efficient mappings (than the use of locks) are possible. most importantly. much of the early discussion focused on the tension between the following two observations. The language itself provided no support for threads. The next C standard is expected to contain a very similar memory model. Third.
  but in the use of undisciplined or “wild shared-memory. at least anecdotally. we point out in prior work12 that other results. versus a language with clear semantics. easily debuggable. But the only available fence instruction constrains all memory reordering around it. there are apparent mismatches. 5 3 | NO. Although the usual immediate result of a data race is that an unexpected. Untrusted code. and such bugs may easily take weeks to track down.” which often takes the form of 98 com municaTio nS o f T h e acm surprising results later during program execution. its lack of any guarantees in the presence of data races and mismatch with current hardware implies three significant weaknesses: Debugging. There is no way to ensure data-race-freedom in untrusted code.acq and st. An unequivocal lesson from our experiences is that for programs with data races. rules to weaken the data-race-free guarantee to better match current hardware.” permitted by current systems. On x86. as through C++ low-level atomics. As discussed. Further.rel. supported by the widespread use of threads despite the inherent challenges. however. and maintainable sharedmemory code. both C++. thus both avoiding the need to specify their behavior and greatly simplifying or elimi- nating the debugging issues associated with data races. the intrinsic advantages of a global address space are. most probably caused by the lack of a well-understood programming language model when the hardware was designed. Many tools to aid such debugging (for example. but should | AU g U ST 201 0 | VO l . Unfortunately. that is. and to a lesser extent Java. and requiring a choice between the two should not be acceptable. The sole purpose of this fence is to prevent reordering of the synchronization store with a subsequent synchronization load. it is very difficult to define semantics that are easy to understand and yet retain desired system flexibility. such as wild branches. these both take us to active research areas. have had to provide less expensive alternatives that greatly complicate the model for experts trying to use them. but no clear definition of what value a shared-memory read may return (the Java case). This may be addressed by translating a synchronization store to an ordinary store instruction followed by an expensive fence. for example. we know of no alternative specification that is sufficiently simple to be considered practical. data-race-free by itself is. A pessimistic view would be to abandon shared-memory altogether. it does not completely eliminate atomicity violations or non-deterministic behavior. Data-race-free was a first attempt to formalize a shared-memory discipline via a memory model. implications for Languages In spite of the dramatic convergence in the debate on memory models. usually a difficult proposition. and thus overly constrains the hardware. We believe the fault lies not in the global address space paradigm. including that involving ordinary data accesses. with no clear offthe-shelf solutions. arguably. As a result. possibly long after the data race has resulted in corrupted data. The only clear path to improvement here seems to be to eliminate the need for going beyond the data-race-free guarantee by: ˲˲ Eliminating the performance motivations for going beyond it. Thus. modern software needs to be both parallel and secure. roughly along the lines of Itanium’s ld. Synchronization variable performance on current hardware. the root cause of such misbehavior is often difficult to identify. are far from satisfying. such a synchronization load is unlikely to follow closely enough (Dekker’s algorithm is not commonly used) to really constrain the hardware. violations of the discipline should not have undefined or horrendously complex semantics. ˲˲ enable the enforcement of the discipline. or that an inconsistent value is written. It proved inadequate because the responsibility for following this discipline was left to the programmer. somewhat limiting their utility. are also possible as a result of compiler optimizations that mistakenly assume the absence of data races. Unfortunately. are also more complex than we would like. We discuss some possible approaches here. Unfortunately. insufficient as a discipline for writing correct. However it fails to prevent reordering of a synchronization store followed by a synchronization load.23 This. We are convinced it is the best model today to target during initial software development. Lessons Learned Data-race-free provides a simple and consistent model for threads and shared variables. The hardware provides sufficient guarantees to ensure that ordinary memory operations are not visibly reordered with synchronization operations. requires a change to the instruction set architecture. in turn motivating additional language-level complexity such as C++ low-level atomics or lazySet() in Java. Unfortunately. and perhaps incomplete value is read. minimally provide sequential consistency to programs that obey the required discipline.review articles on other hardware. that is. A better solution would involve distinguishing between two flavors of loads and stores (ordinary and synchronization). but that requires abandoning security properties promised by languages such as Java (the C++ case). CHESS30 and RaceFuzzer35) also assume sequential consistency. We suspect the current situation makes the fence instruction more expensive than necessary. Accidental introduction of a data race results in “undefined behavior. Moving forward. and ˲˲ Ensuring that data races are never actually executed at runtime. the state of the art imposes a difficult choice: a language that supposedly has strong safety and security properties. However. this model is insufficient for languages like Java. thus this implementation does not prevent the incorrect outcome for Figure 1. While the Java memory model came a long way. and subsequent discoveries of its surprising behaviors. it is almost sufficient to map synchronization loads and stores directly to ordinary load and store instructions. we believe a critical research agenda to enable “parallelism for the masses” is to develop and promote disciplined shared-memory models that: ˲˲ are simple enough to be easily teachable to undergraduates. Second. In practice. Since such races are difficult to reproduce. ensuring sequential consistency in the presence of Java volatile or C++ atomic on current hardware can be expensive. 8 . its complexity.
  review articles
  be caught and returned back to the programmer as illegal; ˲˲ are general-purpose enough to express important parallel algorithms and patterns; and ˲˲ enable high and scalable performance. domainspecific ones. While these solutions go a long way toward easing the pain of orchestrating parallelism, our memorymodels driven argument is deeper—welevel mechanism for atomicity, but the memory model in the presence of nontransactism—an
  99
  Data-race-free provides a simple and consistent model for threads and shared variables. We are convinced that it is the best model today to target during initial software development.
  AU g U ST 2 0 1 0 | VO l. 53 | N O. 8 | c om m u n ic aT ion S of T he acm
  review articles
  summaries are valuable documentation in their own right—they. implications for hardware As discussed earlier, current hardware memory models are an imperfect match for even current software (datarace hard100
  co mm unicaT io nS o f T h e ac m | AU g U ST 201 0 | VO l . 5 3 | NO. 8
  We believe that hardware that takes advantage of the emerging disciplined software programming models is likely to be more efficient than a software oblivious approach.
  ware technology makes this a particularly opportune time to embark on such an agenda. Power and complexity constraints have led industry to bet that future single-chip performance increases will largely come from increasing numbers of cores. Today’s hardware cachecoherent multicore designs, however, are optimized for few cores—power-efficient, performance scaling to several hundreds or a thousand cores without consideration of software requirements will be difficult.oblivious approach. This observation already underlies the work on relaxed hardware consistency models—weand complexity-efficient, softwaredriven com munication. conclusion This article gives a perspective based on work collectively spanning approximately 30 years. We have been repeat-
  review articles
  edly. acknowledgments.
  References), 66–76. 3. adve, s.V. and Hill, M.d. Weak ordering—a new definition. In Proceedings of the 17th Intl. Symp. Computer Architecture, 1990, 2–14.–182. 11. boehm, H.-J. threads basics. July 2009;. hpl.hp.com/personal/Hans_boehm/threadsintro.html. 12. boehm, H.-J. and adve, s.V. Foundations of the C++ concurrency memory model. In Proceedings of the Conf. on Programming Language Design and Implementation, 2008, 68–78. 13. boyapati, C., lee, r., and rinard, M. ownership types for safe programming: Preventing data races and deadlocks. In Proceedings of the Intl. Conf. on ObjectOriented), 85–96. 17. elmas, t., Qadeer, s. and tasiran, s. Goldilocks: a race and transaction-aware Java runtime. In Proceedings of the ACM Conference on Programming Language Design and Implementation, 2007, 245–255.–223.–I364. 22. Ieee and the open Group. IEEE Standard 1003.12001. 2001. 23. Intel. Intel Itanium Architecture: Software Developer’s Manual, Jan 2006. 24. Iso/IeC JtC1/sC22/WG21. Iso/IeC 14882, Programming languages - C++ (final committee draft) 2010; papers/2010/n3092.pdf.), 690–6–102.–455.–455. 33. Pugh, W. and the Jsr 133 expert Group. the Java memory model (July 2009);. edu/~pugh/java/memoryModel/. 34. rinard, M.C. and lam, M.s. the design, implementation, and evaluation of Jade. ACM Transactions on Programming Languages and Systems 20, 3 (1998), 483–5Oriented Programming, 2008, 27–51. 37. shasha, d and snir, M. efficient and correct execution of parallel programs that share memory. ACM Transactions on Programming Languages and Systems 10, 2 (apr. 1998), 282–312. 38. shpeisman, t. et al. enforcing isolation and ordering in stM. In Proceedings of the ACM Conference on Programming Language Design and Implementation, 2007. 39. the openMP arb. openMP application programming interface: Version 3.0. May 2008;. org/mp-documents/spec30.pdf.. Sarita V. Adve (sadve@illinois.edu) is a professor in the department of Computer science at the university of Illinois at urbana-Champaign. hans-J. Boehm (Hans.boehm@hp.com) is a member of Hewlett-Packard’s exascale Computing lab, Palo alto, Ca. © 2010 aCM 0001-0782/10/0800 $10.00
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  and more. knowledge. comment on articles.acm. plus share what’s happening at your ACM chapter.org is the new online hub of XRDS magazine where you can read the latest news and event announcements. and others Interviews and profiles of the biggest names in the field First-hand stories from interns at internationally acclaimed research labs Up-to-date information on the latest conferences.org XRDS.org . HR managers. fellowships. Get involved by visiting today! XRDS. resources. and submission deadlines for grants. and connections that computer science students need to succeed in their academic and professional careers! The All-New XRDS: Crossroads is the official magazine for ACM student members featuring: � � � � � Breaking ideas from top researchers and PhD students Career advice from professors. and more! Also available The All-New XRDS. scholarships. entrepreneurs.acm.Introducing: The ACM Magazine for Students XRDS delivers the tools.acm. contests.
  115 Reasoning About the Unknown in Static Analysis By Isil Dillig. 104 Technical Perspective attacks Target Web Server Logic and Prey on XcS Weaknesses By Helen Wang P. and Alex Aiken AU g U ST 2 0 1 0 | VO l. Thomas Dillig. 114 Technical Perspective Large-Scale Sound and Precise Program analysis By Fritz Henglein P. 53 | N O.research highlights P. Elie Bursztein. 8 | c om m u n ic aT ion S of T h e acm 103 . 105 The Emergence of Cross Channel Scripting By Hristo Bojinov. and Dan Boneh P.
  For ex- ample. Elie Bursztein.com and the attacker (Samy. a more fundamental solution would be to address the root cause of the problem and eliminate any state sharing of independently designed services. and Dan Boneh highlight this problem. The heart of the problem here is to construct such a policy. The XSS problem is amplified in the embedded Web server setting where Web servers co-locate with other services. the malicious file is loaded in the address bar and the malicious JavaScript executes. Because the file system is shared between the Web server and these other file uploading services. Web applications have long suffered cross site scripting (XSS) vulnerabilities. While this may sound obvious. or a P2P service.research highlights Doi:10. the authors talk about reverse XCS vulnerabilities where a Web server’s XSS vulnerability can cause private data from other services to be leaked. running them together creates new security holes because each service has not had the as- The cross site scripting (XSS) problem is amplified in the embedded Web server setting where servers co-locate with other services. Here. lights-out management systems (LOM). 8 . sharing the underlying device resources. mostly along the lines of preventing information leakage by restricting the destinations of the outgoing network messages. A particularly damaging type of XSS is persistent XSS in which the injected script persists beyond a browsing session and across different browsing users. achieving total security throughout a system is rarely trivial when you consider many real-world systems are constantly evolving. this paper offers a valuable lesson in—and interesting read about—system security. The systems examined in the paper are embedded Web servers that have become prevalent for system management and configurations of consumer electronic devices like digital photo frames. 5 3 | NO. For a device with such co-location of services. XSS vulnerabilities of a Web application allows an attacker to inject attacking scripts into the Web application and then the attacking scripts execute with the privilege of the Web site on browsers. the authors uncovered real-world XCS vulnerabilities in a slew of embedded systems. To make things worse. In the following paper.00 104 comm unicaTio nS o f Th e ac m | AU gU ST 201 0 | VO l . sharing the underlying device resources. sumption that the global state (such as the file system) is shared with others. Based on these keen observations. all services can be affected. and so on. Later. “The Emergence of Cross Channel Scripting” (XCS). redmond. several NAS appliances both expose a Web interface for system management and allow file uploading through FTP. To me. The authors note some initial directions for defending against XCS.1145/ 1787234. This is indeed an interesting direction. including several NAS appliances. SMB.1 78 72 5 6 Technical Perspective attacks Target Web Server Logic and Prey on XcS Weaknesses By Helen Wang A syst em I s secure only if the entire system is secure. when an administrator of the device configures the device through the Web interface. and photo frames. the infamous Samy worm exploits an XSS vulnerability in MySpace. Hristo Bojinov. People who viewed Samy’s profile found their profiles infected as did the viewers of their profiles. For example. if any of the services has a security hole. like the file system. helen Wang (helenw@microsoft. even if each of the services is secure on its own. wireless routers. If cross-service sharing is needed. Wa. © 2010 aCM 0001-0782/10/0800 $10. By highlighting the vulnerabilities that still exist. like the file system. the service designer must enable such sharing explicitly. an attacker can upload a file with a specially crafted file name that contains a malicious JavaScript. The authors also explore cellphone-based XCS where the Palm Pre is vulnerable to an XCS attack that injects its payload through a calendar title or content.com) is a senior researcher leading the security and privacy research group at Microsoft research. and networkattached storage (NAS) appliances. in this case) injected a script as part of Samy’s (persistent) user profile.
  XCS is a sophisticated form of cross site scripting (XSS) in which the attack injection and execution are carried out via different protocols. 2009). the user does not need to learn a complicated command-line language. 5 3 | n o. A Type 2 (persistent) XSS enables the attacker to inject a malicious script into persistent storage at the victim site. 420–431. A recent example of such an attack is the XSS Twitter worm that struck in the middle of April 2009. Instead the user interacts with the device through a familiar browser UI. The attacker takes advantage of this lack of restrictions and crafts a filename that contains a malicious script. 9–13. We reveal a series of attacks on consumer and small office electronics. as it effectively prevents security products from scanning such systems and reporting on vulnerabilities or attacks in progress. all the 23 devices we evaluated3 were vulnerable to several types of Web attacks. ranging from networked storage to digital photo frames. which is then interpreted as a script by the The original version of this paper appeared in the Proceedings of the 16th ACM Conference on Computer and Communications Security (Chicago. the vendor does not need to ship client-side software. 1 78 72 5 7 figure 1. it is not surprising that many embedded devices are vulnerable to Web attacks.The Emergence of Cross Channel Scripting By Hristo Bojinov. Type 2 XSS can affect message boards. embedded Web servers are on track to surpass in number general-purpose Web servers on the Internet (Figure 1). and Dan Boneh abstract Lightweight. embedded Web servers will soon outnumber generic Web servers on the internet. the user follows a malicious link to a victim site. For example. In fact. securing Web applications on a consumer electronics device can be difficult due to the large number of supported network protocols and the interactions between them. and are typically used for configuration and management. inTRoDucTion Current consumer electronic devices often ship with an embedded Web server used for system management. The overall opacity of both the software that runs on embedded systems and any state they store further adds to the security risk. 12 and many others. the script can take over the page.5 cross site request forgeries (CSRF). Elie Bursztein. The attacks target Web server logic and are based on a new type of vulnerability that we call cross channel scripting (XCS). When the NAS administrator views the NAS contents through the Web interface. including cross site scripting (XSS). 1. is used to inject a persistent XSS exploit which is activated when the user connects to the Web interface. In this complex environment. This script can then take over the page and perform arbitrary actions on behalf of the attacker. au G u st 2 0 1 0 | Vo l . IL. an attacker can post a message containing a script that is later executed by the browser of every user that happens to view the attacker’s post. manage its permissions through the Web interface. Recall that in a Type 1 (reflected) XSS attack. such as SNMP or FTP. it can introduce considerable security risk due to the large number of potential vulnerabilities in a weak Web application. 8 | c om m u n ic aTion S of T h e acm 105 . They reside in devices entrusted with personal and corporate data. or XCS. a user might upload a file to a network storage device by using the SMB protocol. In an XCS attack a non-Web channel. While browser-based device management is a costeffective and convenient approach.1145/ 1787234 . Moreover. For example. A vulnerability in the site causes an attack script to be embedded into the resulting 300 Doi:10. When an unsuspecting user views a page that contains the script. several NAS devices we examined allow an attacker to upload a file with an almost arbitrary filename via SMB. Growth Internet Embedded (NAS and photo frame only) 225 (Millions) 150 75 Data : -Parks associates -Netcraft 0 2008 2009 2010 2011 2012 2013 HTTP response.2. and second. and eventually share it with his friends through FTP. Market data confirms the success of the browser-based device management paradigm: even when considering only networkattached storage (NAS) and digital photo frame products. embedded Web servers are soon about to outnumber regular Internet Web servers. the device happily sends an HTTP response to the admin’s browser containing a list of file names including the malicious filename. The benefits of providing a Web-based user interface are twofold: first. For example. Nov.13 cross channel scripting: Many of the embedded devices we examined were vulnerable to a type of persistent XSS that we call cross channel scripting.
  g. 3. a two-stage XcS exploit NAS appliances are lightweight servers that provide data storage services to other devices on the network. The interaction between the components may not be completely analyzed. We give examples in Section 4. In the second step the malicious content is sent to the victim by the Web application.. We refer to this as a reverse Xcs vulnerability. ftp_nlist( ) which lists an FTP directory. provide nonWeb cloud APIs for third-party applications which present XCS opportunities. XSS defenses that sanitize data at input time are unlikely to protect against XCS. such as mysql_ fetch_object( ).research highlights browser. 2. In Section 3. and Linksys. such as Facebook and Twitter. can be completely secure in isolation and become vulnerable only when used in conjunction. For instance. For example. 53 | no. Buffalo. Simply inspecting the Web application code and the other service code is not enough to detect the vulnerability. then present real-world XCS attacks and discuss their impact. leading to an XCS vulnerability. The final example uses the calendar protocol to infiltrate the Palm Pre.1. The first example uses file transfer protocols such as FTP to inject a script into persistent storage. We also found a related class of attacks in which a Web vulnerability is used to attack a non-Web channel. We also demonstrate that reverse XCS is a general powerful attack by showing how Restful API-based RXCS can be used to attack very popular Web sites. we briefly cover defenses against XCS and refer the readers to our original paper for a more detailed discussion. XCS and reverse XCS are more likely to affect embedded devices than traditional Web sites because these devices often provide a number of services (e. 3. as discussed in Section 5. such as an FTP server. cRoSS channeL ScRiPTinG in a nuTSheLL An XCS attack is an attack where a non-Web channel is used to inject a script into Web content running in a different security context. Current research on static analysis shows promise in improving the situation in the near future. An XCS exploit can be used to carry out a variety of attacks including figure 2. Detecting an XCS or reverse XCS vulnerability can be difficult because these attacks abuse the interaction between the Web interface and an alternate communication channel. XCS vulnerabilities are harder to detect since they involve multiple protocols. Finally. the number of false alarms would be overwhelming. many Internet Web sites only provide a Web interface and hence are less likely to be affected by XCS. a reverse XCS can be used to reboot a switch and therefore shutdown an entire LAN. Even if all the functions were correctly enumerated. Afterward. The Web application and the other service. Dell. and other file related functions. organization: In the remainder of this article. P2P) which are cobbled together from generic components. First. This includes every SNMP function that reads data. While an XCS exploit is a form of persistent (Type 2) XSS. As soon as the victim accesses the malicious content via her browser. These mechanisms are mostly applied to data acquired from Web traffic. and of course database functions that return a result set. In contrast. Lacie. an XCS exploit can be a stepping stone toward a larger attack on the user’s LAN that aims to assimilate home machines into a botnet4 or to break into the user’s corporate network. for PHP. it is executed with her permissions. we define XCS in more detail. in addition to the obvious file( ). Interestingly. 8 or a user’s keystrokes phishing site code on the server. we argue that a distinction between the two should be made for two reasons. we introduce the concept of reverse XCS and present examples from practice. Static analyzers used to detect XSS (such as Pixy8) do not detect XCS because their taint analysis assumes that the user input is stored in global variables. An XCS attack comprises two steps. This difficulty of detecting and preventing XCS vulnerabilities explains why in every embedded device we examined we were able to uncover XCS problems. The lowend NAS market is very active with over 50 vendors offering products. such as NAS-protected files • Redirecting the user to a drive-by-download site10 or a • exploiting the user’s Ip address for DDoS9 or for proxying the attacker’s traffic On consumer electronic devices. Using taint analysis to detect XCS is difficult because of the large number of possible tainted data sources. The script executes on the admin’s browser giving the attacker full control of the admin session.1 Second. Alternate channels Web Attacker Device User Injection Storage Reﬂection • exfiltrating sensitive data. we present the most interesting XCS attacks we discovered. while in XCS the attack vector is presented through a non-Web channel which is unlikely to sanitize for Web exploits. ReaL-WoRLD XcS We present four case studies illustrating different types of real-world XCS vulnerabilities in popular embedded devices and mobile phones. overview of the XcS attack. In the first step the attacker uses a non-Web channel such as an FTP or SNMP service to store malicious JavaScript 106 com municaTio nS o f T h e ac m | au Gust 2 0 10 | Vol. and the third injects a script into log files. many other protocol specific functions need to be considered. SNMP. the second uses P2P networks. as shown in Figure 2. Web. including Apple. . NFS. such as snmpget( ). large Web sites.
  NAS XCS attacks can be harmful. instead of showing the name of the file. The first method is to keep the second stage payload short by loading the full exploit from an external script on the Internet. The appliance in question allows the user to download BitTorrent files directly by providing an embedded client. 8 | c om m u n ic aT ion S of T h e acm “<iframe onload=’javascript:document. P2P file downloads and RSS flux) gives ample opportunities for implementation oversights that will turn into XCS exploits.head><body><script src =". most vendors build a Web server into them for this purpose. Payload injection through file transfer protocols is a little tricky due to two restrictions enforced by the FTP and SMB protocols: 1. Three of the products we examined suffer from the most prevalent XCS attack: a file is created with a filename specifically crafted to contain malicious payload that gets executed when the admin uses the Web interface to view NAS contents.t2. an attacker constructs a torrent containing a file with a filename that acts as a malicious payload.us/. when viewed by the NAS admin. For example. All five products support the FTP and SMB (CIFS) file transfer protocols.htm’>” The first stage (unpacker) bypasses the charset restriction by avoiding the use of <script></script> to run JavaScript code. Instead. In Figure 3. This client is controlled through a Web interface available on an alternate port (8080): for example. Result from the two-stage XcS attack on a naS appliance. script></. Filenames have bounded length.html>&apos. Nevertheless. As soon as the user downloads the torrent file. we use JavaScript eval( ) to 107 . where the attacker uploads a file with a malicious filename.js". http:. Filenames cannot contain a ‘/’ and as a result we cannot embed an HTML closing tag in them. To avoid the filename length restriction. the administrator has just accessed some shared storage where the attacker has planted a file with a specially designed name. Therefore it is not possible to load an external script directly. we use the onload event of an iframe to execute the code as soon as the iframe is loaded. users can add torrents by supplying .<html><head></. The first step in the attack is a payload injection into the NAS..). 3. steal the admin’s password. To exploit the XCS vulnerability. 2.2. an attacker can inject a malicious filename that.body></. will take over the admin’s browser session.. Each filename contains an encoded slice of the second stage payload.g. well-known vendors and found multiple XCS vulnerabilities in all of them.torrent files.> </. au G u st 2 0 1 0 | Vo l .’ src=’index. or infect the admin’s machine with malware.a52. using HTML escaping. This can be used to exfiltrate protected files on the NAS. A BitTorrent file is basically a list of files to download. there are two possible methods.Since NAS appliances need to be managed over the network. the browser executes a script which accesses a restricted area of storage from the administrator’s session. so that the packed string does not contain a ’/’ and we use the first stage (unpacker) to write into the HTML page. We evaluated five NAS devices from different. we designed a two stage payload using “JavaScript packing”: we encode (pack) our second stage payload. perform a more complex encoding.write(’ &apos. the Web interface displays the list of files in the torrent causing the browser to execute the payload embedded in the malicious filename (as shown in Figure 4). XcS from a P2P channel Another NAS product had a more subtle and potentially more potent XCS exploit hidden in its P2P (Peer-to-Peer) feature. the market pressure to quickly add new features (e. Moreover. Uploading a file into the NAS can be done using a public directory (a public FTP directory is often configured by default). To overcome the second limitation. but without his or her approval (a carefully designed attack script would also cover its tracks. As a result. For instance against one of the devices we used the following two-stage payload: figure 3. along with their hash and tracker URLs that are used to find peers. The first step payload is used to read all the filenames and recompose the payload./. 5 3 | n o. showing the directory contents that the administrator expects). NAS devices inherently support multiple interfaces and thus are primary candidates for XCS exploits. We were able to use this approach on the three devices: in all cases the remote script invocation fit within the necessary length restriction. When the HTML encoding is not sufficient to build an acceptable second stage payload./.
  torrent which contains a popular movie and an additional file that will have the malicious payload in its filename. (The reason for this is to prevent a misconfigured OS from disabling the LOM system. many users will fetch the . then close the current script tag. The P2P XcS attack overview. such IDS. and finally inject an invocation of the attacker’s script. We note that these vulnerabilities are compounded by the fact that the LOM Web site cannot be monitored or filtered by the OS or any software. To address this issue. Moreover. in the form of the Intel vPro technology). The whole sequence is very compact: figure 5.) Lom security mechanisms: Vendors took various security measures to prevent unauthorized access to the LOM system. The attacker controls the admin browser NAS NAS r”. Result from the P2P XcS attack. because the torrent actually contains the real movie. several forms of user authentication. This situation arises both in the data center and on personal computers.research highlights In more detail. the attack. the user has no way of knowing that the torrent contains a malicious payload before the torrent is fetched.“”). The attack works as follows: step 1: The attacker attempts to log into the LOM Web site served by the managed machine. among other things. step 3: Lured by the torrent name.torrent to a popular tracker such as The Pirate Bay. Lom Vulnerabilities: We examined the Web interface on four widely used LOM systems. or antivirus running on top of it.“”. and found several XCS vulnerabilities on all of them. proceeds as follows: step 1: The attacker creates a . he inputs a malicious payload as the user name. no matter how corrupt the software on the machine becomes. figure 4. Tracker 1. Most LOMs provide a Web interface for the administrator to remotely manage the computer. if the payload is sufficiently stealthy the user might never know that an infection took place. There is no need for an authenticated session. fetched from a remote URL. and extensive logging of user activity. The need of physical intervention is problematic.\\/––></script><script src=“”></script> step 2: The logging facility will record this username as-is into the LOM log file on the machine. depicted in Figure 5. which applies almost identically to the products of two different vendors. Users download the torrent Attacker 3. in particular when there is a service level agreement in place. The torrent name by itself is perfectly reasonable and there is nothing to alert the user that it contains a malicious file. These measures include. the malicious payload might first close the function invocation where the user name is passed as an argument. step 2: The attacker seeds and uploads the .3. firewall. where the admin must walk up to the corrupt machine to diagnose and reboot it. As soon as the torrent is fetched the attack begins. all the major hardware vendors have developed firmware components called lights-out management systems (LOM) that can be remotely accessed by an administrator. administrators typically need local access to the console to reboot or reconfigure the machine. This gives the attacker access to over 14 million potential victims.torrent and once that is opened in the NAS Web interface the attacker gains control of the browser session. The logging facility 108 comm unicaTio nS o f Th e acm | au Gust 2 0 10 | Vol. Ironically it is the interaction between the logging facility and the Web interface which is responsible for the worst example of XCS we found. 53 | no. the use of SSL to protect against network attacks. 8 . desktops. For example. is possible by simply accessing the Web interface on the affected system. and laptops (every computer that uses an Intel Core2 chipset has one. In this attack. Instead of trying to guess the login. as that would defeat the purpose of LOM. LOM is found on servers. Log-based XcS Lights-out management systems: When an operating system crashes or becomes corrupt. The payload writes “XcS attack” in the page. The attacker uploads the malicious torrent 2. Abusing the Logging Facility: This XCS uses log injection6 to inject a script into persistent storage on the device. The attack. 3. because it drastically increases downtime.
  0. Note that once again firewalls can’t prevent this kind of attack as the user browser is used to infect the frame and exfiltrate the data.1. As presented in Figure 8. Infection: The infection phase aims to store the ghost into the photo frame. Figure 7 depicts how the attack works: first the attacker injects malicious code to a site that the user will visit. using the Web server embedded in a photo frame. The second combines XCS and reverse XCS to exfiltrate protected data stored on a NAS through a P2P network. then there is a good chance that. the malicious code performs a port scan to detect if the photo frame is present in the user LAN. the photo frame is vulnerable to CSRF and XSS attacks. On the Palm Pre. for instance. We illustrate reverse XCS using two real-world vulnerabilities. a photo frame is present. Then the user browser runs the malicious code and infects the photo frame with the ghost (see Figure 8). To do so. The attacker can also infect the administrator’s computer by directing the browser to a malware site.” The ghost will be reflected on the photo frame main page that displays the current photo and provides controls to change it. a recent report7 shows that the Palm Pre is vulnerable to an XCS attack that injects its payload through a calendar title or content. Modern smartphone platforms such as Google’s Android and Palm’s WebOS use HTML and JavaScript to build application views. Since it might happen that the user is already logged in.0/24. with a default password. Second. in the settings page it is possible to use the frame name input to inject and store a nonescaped payload: our “ghost. Finally. Given the number of services and protocols supported on these elegant devices. The result of the Lom log injection attack. Finally a second CSRF attack is used to inject the ghost into the photo frame name. this way we only end up overwriting our ghost which is not an issue—and we are able to infect frames with custom passwords as long as the user is already logged in to them.168. We added a visible debug trace at the bottom of the interface. As most embedded devices that we evaluated.4. the ghost executes and exfiltrates the current photo which is stored on an SD card. figure 7. More precisely. for each open port found a CSRF attack is used to log in using the default password. Indeed. The ghost in the photo frame A photo frame built by a major consumer device vendor has an embedded Web server on port 5050. ReVeRSe XcS: DaTa eXfiLTRaTion anD BeyonD A reverse XCS attack uses the Web interface to eventually attack a non-Web channel. In the worst case. if this port is open. 8 | c om m u n ic aT ion S of T h e acm 109 . three steps are required. Since the port used by the photo frame is unusual. the attack can be broken into two phases: infection and execution. it tests whether port 5050 is open on a set of probable internal IPs: 192. 4. cellphone-based XcS XCS attacks are not limited to Web management interfaces. 4. The first exfiltrates photos stored on an SD card by figure 6.does not escape data written to the log file to prevent Web attacks.10 The result of this XCS attack on the Dell Remote Access Controller is shown in Figure 6 where an image is injected onto the administration page. 3. To do so. a more robust technique is to first do the CSRF used to inject the ghost then try to log in and finally re-inject the ghost. XCS is an important concern. The malicious payload can be used to add a rogue administrator account to the LOM and thus grant full access to the attacker. step 3: The malicious payload is executed by the LOM admin’s browser when she views the log. the entire GUI is built using JavaScript and HTML on top of Webkit. each time the user visits the photo frame Web server. 5 3 | n o. despite the fact that the log file can be viewed via the Web interface. Attacker site Step 1 Iframe injection Infected site Infected site Step 2 User browsing Step 3 User browser injects the ghost Browser Firewall Browser Device Step 4 Ghost abuses the browser to stealth data au G u st 2 0 1 0 | Vo l . The ghost in the photo frame overview. The main application for this class of attacks is to exfiltrate data that is not supposed to be shared either because it is protected by an access control mechanism or because it is not supposed to be shared at all. First. for example.10 Figure 9 shows the ghost in action.
  The first challenge was addressed by using a loader: the injected code is not the ghost itself but rather a payload that will ask the browser to load the ghost as an external JavaScript. 53 | no. malicious Web site11—is not an issue here as posting data from the legitimate site to the malicious one goes in the opposite direction and is currently fully unrestricted: . we had to exfiltrate it while keeping the regular frame code running. request the ghost as a new script and resume the function. 3. Resuming was required because otherwise the frame control would have been broken. This is not supported directly by XMLHTTPRequest. The second challenge was more difficult because the injected ghost is reflected in the middle of a JavaScript function in the variable name. 8 This code works as follows: first it injects in the page an invisible form named f (used to post exfiltrated data) and an iframe named uploadtarget into the Web page (line 1). }</script> <script src=“. execution: The four challenges we faced in implementing a ghost designed to exfiltrate data were: 1. The ghost in action: a photo has just been exfiltrated.research highlights 2. Note that the same origin policy—the mechanism which protects the user’s session to a legitimate Web site from being exploited by a different. data = fetch(page).js”> </script><script> function n() {var frame Name =” figure 8. Reload(). This payload is designed to close the variable. payload size: The size of the payload that can be injected is limited. This iframe is used to take advantage of the ability to control through JavaScript the iframe in which the form f action will be executed. data = rencode(data).target = ‘upload_target’. Posting into the iframe is mandatory to prevent the redirection of the entire page that will break the exfiltration loop and alert the user. post(data). the function and the script. otherwise the browser will stop the execution. 4. preventing the exfiltration. To deal with the third and fourth challenges which are closely related. data = decode(data). Javascript errors: The code must not trigger a single JavaScript error.. 110 co mm unicaTio nS o f T h e acm | au Gust 2 0 10 | Vol. redirectPost(). we had to come up with a new method that uses AJAX tricks and a manipulation of the XMLHTTPRequest object in a novel way. Fetching data: We had to find a way to fetch binary data. The ghost attack executed on a photo frame. Therefore the following payload was injected to the frame: name “. exfiltrating data: Once the data was loaded in memory. The sketch of the code used as a ghost is depicted below: injectIFrame().f. Accordingly the second step of the ghost (line 2) is to redirect the form f action to our invisible iframe by using the following JavaScript command: document. Phase 1: infection Port scan Login CSRF Ghost injection Phase 2: execution Inject payload Fetch data Post data figure 9.
  5 3 | n o. moreover. 8 | c om m u n ic aT ion S of T h e acm 111 . This combination allows to bypass current CSRF defenses because they all rely on the same origin policy in one way or another. The standard way to post a file is to use a file input field that the user will use to select which file to post. On the other hand. The ghost in the P2P client Recall from Section 3. The user is oblivious to the attack because. RESTful APIs are becoming the ubiquitous way to interact with cloud services. who has control over the Web interface. E-bay. and. In Firefox. he will be completely unaware of the attack. Therefore we had to come up with an alternative approach. offer this kind of API. the attacker can use the P2P client to exfiltrate NAS content through the P2P network. since the XCS injection vector is not Web based. the same origin policy does not apply to our attack because we use an infected page to attack other pages within the same domain.charset=x-user-defined”) the attacker to hide his malicious activity. In this section.such posting is assumed to be under the control of the request originator. we present RXCS vulnerabilities that make use of the APIs provided by large social networking Web sites. Many popular cloud services. To go around this issue. the problem is to acquire the data that will be exfiltrated. we need to find an alternate method as we don’t have the user’s cooperation.2 that some devices have an embedded P2P client. Based on the observation that the files we want to exfiltrate are located in the same domain as the ghost. Combined with the P2P XCS approach from Section 3. and reload the interface to exfiltrate the next photo. The last problem we had to deal with was the reload timer used in the photo frame: every 500 ms the page was reloaded.3.com/users/show/elie. then the JavaScript adds it by hijacking the Web function used to add a torrent file. this client can be abused by a reverse XCS to seed illegal data and exfiltrate data. Back To The WeB: ReSTfuL RXcS Up to this point we have intentionally avoided direct references to product vendors. The same origin policy is once again unable to prevent this behavior because our ghost acts here as an autoimmune disease: an infected page attacks the rest of the same Web site. Bypassing cSRf defenses Another application of reverse XCS. 4. The rest of the ghost code is straightforward: it is used to decode the XHR custom encoding (line 4). uses it to insert torrents that he wants the NAS to seed for him. reading its result and extracting the token value to construct dynamically the form that will be used to perform the CSRF attack. is to use the infected page to attack the same site using XHR or CSRF. we address the challenges posed by two specific social networking sites. pure Web defense mechanisms have no impact on XCS attacks. re-encode the file in base64 (line 5). having full control of the page allows. the Twitter RESTful API allows anyone to query user profiles in XML format by issuing the following call: Using the XHR object with this override allows the ghost to fetch any type of file and load it into a JavaScript variable. In this section. The idea behind the attack is as follows: the attacker. At this point. it is not possible to manipulate the file input with JavaScript for obvious security reasons. Moreover. Note that again a firewall cannot prevent this attack since the client is authorized to download its own torrents. including Twitter. This can have two purposes: on the one hand he can use the NAS capacity and the user bandwidth to seed illegal files on his behalf. which is a natural extension of previous attacks. it is possible to override the mime type used in an XHR and request a custom charset encoding by using the method: overrideMimeType(“text/ plain. and so using solely XHR is not sufficient. Google and Flickr.2. The direct conclusion of this is that any device subject to an XCS is also subject to CSRF attacks regardless of the CSRF defense it implements. post it (line 6) in the iframe. If one file is not seeded. By playing with the CSS display attribute the attacker can mask his malicious torrents and display only those requested by the user. for example. Facebook. The key challenge was to find a way to allow the ghost to control which files need to be seeded. The use of secure tokens can be defeated by sending an XHR request to the page. 5. The two prominent defenses against CSRF2 are to verify the HTTP header referer/origin and to use a hidden secret token. this is a way to seed illegal data on a massive scale. Of course this behavior was breaking the ghost activity so a part of the ghost is used to override the timeout value with a huge number and when the photo is exfiltrated the reload method is explicitly called by the ghost. as in the photo frame case. In other words. One difficulty with using this method is that the XHR object is not designed to fetch binary data—only text. So unless the user views the page source. We feel that being concrete will help illustrate the problems in each environment without having to point at any third-party application developers. To achieve this. For example. we came up with the idea of using an XHR (XMLHTTPRequest) to load the data inside a JavaScript variable (line 3).2. In this way the ghost is able to transparently accommodate any upload speed. Besides being an XCS injection vector. 4. Of course in our case. we came up with the idea of changing the http request header and more precisely the Mimetype encoding. we used an externally loaded JavaScript that keeps track of the current files seeded by reading the client page and comparing it to a list supplied by the attacker. Checking the HTTP header is useless in the context of XCS because the request comes from the same domain. however.xml au G u st 2 0 1 0 | Vo l . the problem discussed has a much wider scope.
  such as plain text event logs. It is sufficient to add malicious payload in the movie profile data: this payload can then get reflected to all Facebook users that use the application. I am still loving it :) #woot </text> … </user> The problem here lies in the fact that there is implicit trust between the third-party application and the cloud service. 5. Moreover. while application developers often make assumptions about the safety of that data. CSP. and raise an alarm if tainted data is displayed in a Web page without first being sanitized. used by Twitter for instance. before it is written to persistent storage at the site.im</url> <protected>false</protected> … <text> Second time I see the SMS fuzzing talk. this might be used to bypass Facebook security policies. 53 | no. This is unlikely to mitigate an XCS vulnerability because the malicious content is injected via a non-Web channel. interactions with cloud services rely on many assumptions that are not properly formalized. First. is to sanitize all user data at input time. Consequently. 14 This approach must taint all input channels into the Web application.3 we proposed a defense called SiteFirewall. it is not difficult to find a Twitter application that is vulnerable to RXCS injection.research highlights This call will return the following formatted data that can be subsequently processed by the third-party application to compute statistics or store in a database for later use. Twitter RXcS Twitter has the opposite filtering policy compared to Facebook: escaping is performed at input time so all data 112 comm unicaTio nS o f Th e ac m | au Gust 2 0 10 | Vol. The source of the problem is that Facebook trusts third-party applications to properly handle API data. we have only begun to address some inherently server-side problems. facebook RXcS Facebook escapes at display time which means that the data provided to third-party applications is not escaped. In particular. However. Tracking data life cycle can easily miss some XCS channels or fail to taint XCS content.1. We give two examples.1. this defense fails to work directly on non-Web raw data. In Figure 10. If an application wants to deal with “raw data” it has to unescape the data before processing it. and other mechanisms generally attempt to block a Web site running in a browser context from executing operations that involve other Web sites and could potentially either access or exfiltrate private data. In theory. This unescape. it is likely that some applications will display the data or store it. static analyzers can perform flow analysis to detect potential XCS. SiteFirewall. understanding the trust model behind this exchange and how to combine filtering policies are open questions that we want to address in future work. Of course. it is sufficient to add the <script> tag to them to get that text reflected to an application. Indeed. a Twitter third-party application attack illustrated. Suppose you have an application that displays information about Facebook users’ favorite movies. When the application finds the string (and thus the planted message). applications are not supposed to store any user data. defining what safe data means is far from obvious and each cloud service has its own sanitization policy which is often not explicitly documented. To give an example. In our original paper on XCS. <user> <id>57142771</id> <name>Elie Bursztein</name> <screen_name>elie</screen_name> <location>Palo Alto</location> <url>. and compared it to other current developments in Web security. However. Third-party application developers assume the cloud service provides “safe” data. In principle. when the application wants to output the data. one such application is asked to search for a string. it has to reescape the data in its own way. 5. it shows the message in the browser after processing it and the embedded payload is inadvertently executed. which usually does not sanitize for Web exploits. 6. While recent work on XCS defenses has focused primarily on the browser. even if Facebook may monitor API usage to prevent terms of service violations. we point out that attacking a vulnerable third-party application can be done by noting that all the profile details from interests to music and movies are not escaped. As one can see. provided to third-party applications is HTML escaped. reescape process is tedious and error-prone. 8 . device vendors must figure 10. Facebook’s terms of service say that third-party applications are not supposed to directly output the data fetched from the API but rather use the Facebook output functions. SOMA. This inconsistency between expected data and supplied data can result in RXCS. This is problematic if these data are also used by other applications that are not Web based such as a back-end statistics analyzer or an IDS. Another popular XSS defense. including all persistent data on the device. Similarly. DefenSeS aGainST XcS One defense against XCS is to ensure that all data sent to the user’s browser is properly sanitized. which is the label of a message planted by the attacker.
  bojinov. C. stanford. Jovanovic. complex embedded application logic and state need to be more visible. 12. In Proceedings of ACM CCS '08 (2008). In Proceedings of HotBots’07 (2007).mozilla. d. 2. 9.pdf.edu).acm. e.org/careercenter ◆ ◆ ◆ ◆ ◆ The ACM Career & Job Center offers ACM members a host of benefits including: A highly targeted focus on job opportunities in the computing industry complied from hundreds of sources.. Dan Boneh (dabo@cs. d. Kirda. and users are enabled to make and execute decisions about managing their networked private data..stanford. V. K. lee.l. dagon.. Hansen. e. techcrunch. Kruegel. 10. J. References 1.com/2009/04/11/twitterhit-by-stalkdaily-worm/. the ghost in the browser analysis of Web-based malware. In CCS ‘09: Proceedings of the 16th ACM Conference on Computer and Communications Security (new york. d. usa. 5. xie.t. K. Javascript security: same origin. M. G. Modadugu. anagnostakis. 2007. C.stanford. stanford university. Cova. concLuSion Networked appliances are not as secure and harmless as they are often assumed to be. We hope that we have at least made the first step toward that goal. the Web community needs to recognize that embedded Web sites can have fundamentally different use models from those usually seen on the Internet: we have to enable these two paradigms to coexist securely. J. static detection of security vulnerabilities in scripting languages. n. s. Second. stanford. P.com/wps/portal/kb/na/ pre/p100eww/sprint/solutions/ article/50607_en. august 2001.palm. hristo Bojinov (hristo@cs. In Proceedings of the CCS (2006). In IEEE Symposium on Security and Privacy (2008). d. The advent of browser-centric Web 2. Ca. In In Proceedings of the USENIX Security Symposium (2006). 3. and the Packard Foundation. Jovanovic. Kirda.stanford.au/ assets/downloads/sIFt-log-InjectionIntelligence-report-v1-00. www. stanford. C. © 2010 aCM 0001-0782/10/0800 $10.. twitter worm. Vigna. d... 420–431.. s. e. giving rise to XCS. Wiley.. and much more! ➜ ➜ The ACM Career & Job Center is the perfect place to begin searching for your next employment opportunity! Visit today at. xCs: cross channel scripting and its impact on Web applications. stanford university. In IEEE Symposium on Security and Privacy (2006).. Third. this work is supported by the nsF. akritidis. august 2009.. In Proceedings of the 23 Annual Computer Security Applications Conference (ACSAC) (2007). Puppetnets: Misusing Web browsers as a distributed attack infrastructure. saner: Composing static and dynamic analysis to validate sanitization in Web applications. a. 4. Elie Bursztein (elie@cs. Web: http:// kb... J. ruderman. 2007. log injection attack and defence. barth. 6. stuttard. The Web Application Hacker’s Handbook: Discovering and Exploiting Security Flaws. d. Pinto. ny. Jackson. software update information for palm pre sprint p100eww. Web browsers are capable of dealing securely with different classes of Web applications. Harris. XSS Exploits: Cross Site Scripting Attacks and Defense.. aiken. which would enable vulnerability scans either from the same host (in the case of LOM) or over the network (for appliances not running a general-purpose OS). 7. aCM. Mavrommatis. 2007. r.html. P. n. Gu. syngress. V. Ca. H. antonatos. Wang.. M. Provos. W. 8 | c om m u n ic aT ion S of T h e acm 113 . 2009). a. n. lee. dHs. rager. C. robust defenses for cross-site request forgery..exercise greater care in selecting Web server implementations and demand better security from external embedded Web server developers and their own engineering staff. Fogie. balzarotti.. lam.acm.sift. 11. http:// www. bursztein.G.. Grossman...edu).html.edu)... Mitchell. Ca.com. n... a..org/careercenter au G u st 2 0 1 0 | Vo l . stanford university. y. 14.. Mcnamee.00 Announcing ACM’s Newly Improved Career & Job Center! Are you looking for your next IT job? Do you need Career Advice? Visit ACM’s newly enhanced career resource at:. 8.. P. a taxonomy of botnet structures.0 computing has amplified the scope of attacks possible via embedded devices. Grzelak. Felmetsger. Pixy: a static analysis tool for detecting Web application vulnerabilities. Petkov.. G.. Palm.. 7.. t. 13. 5 3 | n o. boneh.org/projects/security/ components/same-origin. Kruegel. There is much work to be done before hardware vendors start to routinely design and test for security.
  The requirements look reasonable: Given an input program we want to check whether it has some desired “runtime” (behavioral) property. make it (or its negation) hold for all programs.dk) is a professor of Cs and head of the algorithms and Programming languages Group. This paper illustrates that the days of feasible.1 78 72 5 8 Technical Perspective Large-Scale Sound and Precise Program analysis By Fritz Henglein you ARe gIVen a program. other programs analyzed before or simultaneously. Their execution requires care. and ˲˲ Require an exact answer: yes if the property holds. The following paper provides a powerful sound static analysis framework for C programs and nontrivial behavioral properties. no if it doesn’t. The authors contend it is important for practical precision to model the results of internal choices as unknowns: once a choice is performed the result is unknown.a ˲˲ A nontrivial behavioral program property. Their key insight is we are typically only interested in whether an abstracted function has a property for all possible sequences of internal choices in its body or for some particular sequence. which require interprocedural data flow analysis. Will it crash? Is it subject to a spoofing. but every time we need the value it is the same. Transaction of the American Mathematical Society 74 (1953). Java. This leaves only the third possibility: ˲˲ Allow approximate answers. respectively existentially bound. for example. 5 3 | NO. can be found without drowning them in false positives. for example. they show that null derefence bugs. as the authors explain aided by their selection of an illustrative fragment of C and a running example developed from source code to analysis result. equivalence of regular expressions. allow the program analysis to return “don’t know” answers or to run forever (which is practically tantamount to “don’t know”). which allows guaranteed optimization of regular expression matching. We can think of these steps as in- ternal choices: the abstract model just performs the internal choices without external control. symbolic fixed-point computation to compute closed forms for recursive constraints. 358–366. and other factors completely extrinsic to the program at hand. sound. or injection attack? Is this part of it dead code? Can I replace that code fragment with a more efficient one? Which exceptions can arise from calling this function in that context? Does this variable always contain the same value? All of these questions require program analysis: We want to know whether program code (the input to the analysis) has a specified property. whichever way you catch it. Classes of recursively enumerable sets and their decision problems. In other words.00 | AU gU ST 201 0 | VO l .1 Consequently. Haskell. we need to give up at least one of these requirements to escape undecidability. This abstraction is familiar from software model checking. Program analysis is inherently difficult. university of Copenhagen (dIKu). 114 co m municaTio nS o f T h e acm against arbitrary programs thrown its way it forces the programmer to provide what amounts to a checkable proof that the program has the desired property. and finally constraint solving. Since a “don’t know” answer constitutes a false positive whenever the (desirable) property really holds. denmark. © 2010 aCM 0001-0782/10/0800 $10. buffer overflow.000 warnings (“don’t know”) of which only 10 turn out to be bonafide bugs may not be practically useful. Very often we need to analyze general-purpose programs without the privilege of foresight provided by the programmer and enforced by the programming language. Fritz henglein (Henglein@diku. This is what static type systems and emerging technologies such as proof-carrying code can provide. A bug is a bug. This is captured by logical constraints for the input-output relation of a function where all the internal choices are universally. however. the argument goes. is a particular fragment dead code. the integers may be replaced by a single abstract value (representing all integers) and the result of an arithmetic comparison may be approximated by a nondeterministic choice of a Boolean value for the result. Take the following ingredients: ˲˲ A Turing-complete programming language such as C. The authors show that a precise compositional program analysis that is context-sensitive and pathsensitive is possible for huge code bases of central importance to our day-to-day computing infrastructure. ˲˲ Remove Turing-completeness: Languages of restricted expressive power may have decidable nontrivial behavioral properties. build it into the programming language. The paper outlines conceptually independent and generally applicable steps assembled into a solution pipeline: quantifier elimination. Gordon rice. The challenge of bug hunting in large C code bases has seen the rise and application of techniques that are neither sound nor complete nor even stable: their result may depend on the machine load. In particular. that is. bringing together and leveraging techniques ranging from the foundation of (Boolean) logic to state-of-the-art SAT-solving. H.research highlights Doi:10. does a program de-reference a null pointer. They constitute a cunning turning of the tables: Instead of program analysis fighting an uphill battle a A programming language is Turing-complete if it is possible to write an interpreter for Turing Machines in it. a key challenge is designing a program analysis to be sufficiently precise for its intended application so it does not drown its user (whether human or another system such as a compiler) in false positives: An analysis returning 1. well-specified.1145/ 1787234. and sufficiently precise static program analysis for bug hunting even in huge code bases are not numbered. for example. Reference 1. Their starting point is an abstract model of a program where infinite domains are finitely approximated and certain steps are replaced by nondeterministic steps resulting in unknown results. or indeed both. that is. 8 . ˲˲ Make the property trivial. department of Computer science. But they constitute an explosive mix: Any such problem is undecidable—no program can solve it.
  Second. The many tool-based approaches to the problem can be grouped roughly into two categories. may also need to treated as an unknown by the static analysis. there is no free lunch: Soundness usually comes at the cost of reporting false positives (i. sound static analyses have the advantage of never missing any potential errors. this input appears as a nondeterministic environment choice to the static analysis. spurious warnings about error-free code) because static analyses must approximate some aspects of program behavior. approach to dealing with unknown values in static analysis. For the matching property to be violated. but imprecise. including an entire operating system. In contrast. static analysis always has some imprecision built in. it must be the case that the value of input is ’y’ on line 2. Thomas Dillig. ACM. a static analysis discovers properties that hold for all possible inputs. such as the value of user input or network state. inTRoDucTion Preventing software errors is a central challenge in software engineering. if the chosen program abstraction cannot express nonlinear arithmetic. sets. the result of receiving arbitrary data from the network or the result of reading operating system state are all unknowns that need to be treated as nondeterministic environment choices by the analysis. in our experience. the value of a “complicated” expression. since lists. It is our impression that if the question is considered at all. a key challenge for static analysis techniques is achieving a satisfactory combination of precision. But two observations have changed our minds: First. it is still possible to glean very useful information about how such statically unknown values may or must influence computation. enabling us to apply the technique to very large programs. we usually want to guarantee the analysis terminates even if the program does not. and trees may have an unbounded number of elements. a sound static analysis concludes a program is error-free only if the program indeed has no errors. unknown values are astonishingly pervasive when statically analyzing programs. analyses that do a poor job handling unknown values either end up being unscalable or too imprecise. Similarly. and Alex Aiken abstract Static program analysis techniques cannot know certain values. We give a method for integrating such nondeterministic choices with an expressive static analysis. this is the approach we have taken ourselves in the past. Hence. This goal of obtaining satisfactory precision is further complicated by the fact that certain values are simply unknown statically: For example. if a program queries the user for an input. A static analysis cannot simply carry out an exact program simulation. many static techniques do not precisely model the data structure’s contents.Reasoning About the Unknown in Static Analysis By Isil Dillig. useful information can be garnered from such unknown values is not much discussed in the literature. The question of what. We show experimentally that the resulting solved forms are concise in practice. 1. there is exactly one matching call to fclose. Consider the following code snippet: 1: 2: 3: 4: char input = get_user_input(). if any. such as coef*a*b+size.e. if(input == ’y’) fclose(f). Suppose we want to prove that for every call to fopen. While such unknown values need to be treated as nondeterministic choices made by the program’s execution environment. we cannot solve the resulting recursive constraints directly. 5 3 | n o. there are always calls to external functions not modeled by the analysis as well as approximations that lose information. if nothing else. but we give an exact method for answering all may and must queries. Reading an element from a data structure is modeled as a nondeterministic choice that returns any element of the data structure. Dynamic analysis techniques discover properties by monitoring program executions for particular inputs. Complete. standard testing is the most commonly used form of dynamic analysis. process_file_internal(f). Interestingly. au G u st 2 0 1 0 | Vo l . Similarly. and Scalable Path-Sensitive Analysis” and was published in the Proceedings of Programming Language Design and Implementation (PLDI) 2008. 8 | c om m u n ic aTion S of T h e acm 115 . it is left as an engineering detail in the implementation. Even in the special case where all program inputs are known. we now believe a systematic approach for dealing with unknown values is a problem of the first order in the design of an expressive static analysis.. but. We begin by informally sketching a very simple. at analysis time. soundness. For example. This approximation is inevitable as analyzing even very simple properties of programs’ behavior is undecidable. For these reasons. 1 78 72 5 9 arise from approximating program behavior. Thus.1145/ 1787234 . unfortunately. and scalability by reporting as few false positives as possible while still being sound and scaling to real systems. static analyses still need to deal with unknowns that Doi:10. if(input == ’y’) f = fopen(FILE_NAME). Unlike dynamic analyses. at least. but the value of input The original version of this paper is entitled “Sound.
  the substitution [T/a] models that on the recursive call. Thus. Thus.\n”). the user input must either be ’y’ (term b = ’y’ and line C) or it must not be ’n’ (term ¬(b = ’n’) and line D) and the recursive call on line G must return true (term P[T/a]). so is the formula. the same problem arises both for loops and recursive functions. In practice. Observe that this strategy of introducing choice variables is a refinement over the previous approach because two distinct environment choices are modeled by two distinct choice variables. For instance. which is good because we never know a priori which parts of the program are important to analyze precisely and so introducing unnecessary imprecision anywhere in the model is potentially disastrous. b². in fact. and the analysis would erroneously report an error. Observe that because the function is recursive. a. the predicates é = ’y’ (which should be read as: ’y’ is equal to some element of values represented by é) and é ’y’ (which should be read as: ’y’ is not equal to some element of values represented by é) are simultaneously satisfiable. hence it is identified by a choice variable b. Hence. under which query_user returns true a (abbreviated T) in any calling context. The condition. but it is potentially different from any other choice on subsequent recursive calls. establishing that the call to fopen is matched by a call to fclose. P. co m municaT io nS o f Th e acm | auGust 2 0 10 | Vol. . In the term P[T/a]. On the practical side. it is easy to see that there is no finite nonrecursive formula that is a solution of the recursive equation (*) because repeated unfolding of P [T/a] introduces an infinite sequence of fresh choice variables b ¢. then the analysis needs to ask may questions. The variable feature_enabled. E: printf(“Input must be y or n! F: Please try again. b and b¢. We represent feature_enabled by an observable variable. 53 | no. The insight is that the use of choice variables allows the analysis to identify when two values arise from the same environment choice without imposing any restrictions on their values. Furthermore. But the model has more information than needed to answer most individual questions we care about. While this function would typically be written using a loop. Consider the following function:a Suppose we want to know when query_user returns true. however. it leads to two difficulties—one theoretical and one bool query_user(bool feature_enabled) { A: if(!feature_enabled) return false. is then given by the constraint: P. The term a = T captures that the function returns true only if feature_enabled is true (line A). but unknown. one simple approach is to represent the unknown value using a special abstract constant é. is definitely not a nondeterministic choice. indicating that we do not know what choice is made. D: if(input == ’n’) return false. Now. The return value of get_user_input is statically unknown. A more precise alternative for reasoning about unknown values is to name them using variables (called choice variables) that stand for a single. Therefore.research highlights is not ’y’ on line 4. every call to malloc in a C program appears as a nondeterministic choice returning either NULL or newly allocated memory. but less precise. P[T/a] unfolds to: (T = T) Ù (b ¢ = ’y’Ú (¬( b¢ = ’n’) Ù P[T/a] While the equation (*) expresses the condition under which query_user returns true. While this latter strategy allows for more precise reasoning. B: char input = get_user_input(). the binding P. we are usually interested in only two kinds of 1-bit decision problems. the number of choice variables grows rapidly with the size of the program. such as “May this program dereference NULL?” or “May this program raise an exception?”. Thus. the recursive definition means it is not immediately useful. b¢². value.b reminds us that b is a choice variable. and we use a recursive function because it is easier to explain. As a result. Choice variables allow us to create precise models of how programs interact with their environment. it is not always possible to give a finite closed-form formula describing the exact condition under which a program property holds. . 8 116 . for example. then the analysis needs to ask must questions. G: return query_user(true). if we introduce the choice variable b for the unknown value of the result of the call to get_user_input on line 1. When the equation is unfolded to perform the substitution [T/a] we must also make the environment choice for b. } practical—that the simpler. . real programs have many sources of unknowns. C: if(input == ’y’) return true. Finally. such as “Must this memory be eventually freed?”. the constraint characterizing the failure condition is b = y Ù b π y. strategy does not suffer from. it is important to avoid tracking choice variables whenever they are unnecessary for proving a property. Furthermore. . The most general choice we can make is to replace b with a fresh variable b¢. é is not a particular unknown but the set of all unknowns in the program. If one is interested in proving that a program does not do something “bad” (so-called safety properties). provided by callers of this function. overwhelming the constraint solver and resulting in poor analysis scalability. which is unsatisfiable. but not equal to ’y’ at line (4) (or vice versa) cannot be ruled out. program paths where input is equal to ’y’ at line (2). the formal parameter a is replaced by actual parameter true. if one is interested in proving that a program eventually does something good (so called liveness properties). all of which are represented by é.b = (a = T) Ù (b = ’y’Ú (¬(b = ’n’) Ù P[T/a] = T)) (*) This formula is read as follows. On the other hand. it cannot represent two distinct values at the same time. Hence. may and must queries. Our solution to both the theoretical and the practical problems can be understood only in the larger context of why we want to perform static analysis in the first place. Since the value of the input is unknown. assuming we do not reason about the internal state of the memory management system. while a choice variable b may represent any value. as its value is determined by the function’s caller. programs may have multiple sources of unknown values.
  our goal is to compute the constraint under which each function returns constant Ci. then the program is not guaranteed to be error-free. 2. the aggregate behavior of the function can be precisely summarized in terms of only observable variables for answering may and must queries. These constraints are of the following form: Definition 1 (Constraints). Hence. do not grow in the size of the program.. and observable variables a representing function inputs provided by callers. Boolean-valued expressions where the unbound variable y models a nondeterministic choice is described by the equation: AU g U ST 2 0 1 0 | VO l. In this paper. we model unknown values by references to unbound variables. let bindings and comparisons between two expressions. fSCñ for each initial equation. constraint variables with a substitution P[Ci /a]. . = F. our technique first generates a recursive system of equations. allowing our technique to scale to analyzing programs as large as the entire Linux kernel. and Ø. We then eliminate choice variables from this recursive system to obtain a pair of equisatisfiable and equivalid systems over only observable variables. if P. . and describes the function f that returns C1 if its input has abstract value C2 and vice versa. 53 | N O. In this language. abstract values Ci.. Observe that this language has an expressive set of predicates used in conditionals. most surprisingly. can be used in any calling context of f. false. . to answer may and must questions about programs precisely. we consider the program properties “May a given function return constant (i. any free variables occurring in a function body are choice variables. Constraints express the condition under which a function f with input a returns a particular abstract value Ci. then: P[Ci /a] = F [Ci /a][ / ] ( fresh) This renaming is necessary both to avoid naming collisions and to model that a different environment choice may be made on different recursive invocations. must questions are naturally formulated as validity queries: If a formula representing the condition under which something good happens is not valid. . So. we consider a family of finite abstractions where each variable has one of abstract values C1. this language is sufficiently expressive to illustrate the main ideas of our techniques: can be composed using the standard Boolean connectives. we do not necessarily need to solve the exact formula characterizing a property. C for clarity. and recall that the vector of choice variables named with the P variable is replaced by a vector of fresh choice variables in each unfolding of the equation. We also apply this technique for finding null dereference errors in large open source C applications and show that this technique is useful for reducing the number of false positives by an order of magnitude. As a final example. 8 | c om m u n ic aT ion S of T h e acm 117 . the function define f(x) = if (y = C2) then C1 else C2 Expressions are true. The final result is a bracketing constraint áfNC. fRom PRoGRamS To conSTRainTS As mentioned in Section 1. so the condition under which some program property holds may be nontrivial. The substitutions [Ci /a] on constraint variables are used for the substitution of formals by actuals. . The key idea underlying our technique is that while choice variables add useful precision within the function invocation in which they arise. variables x. dataflow values. abstract value) Ci?” and “Must a given function return constant Ci?”. while simple. . Hence. corresponding to closed-form strongest necessary and weakest sufficient conditions. To be specific. choice variables b whose corresponding abstract values are unknown. function calls. a. Because the values of inputs to each function f are represented by variables a. Constraints F are equalities between symbols (s1 = s2). Symbols s in the constraint language are abstract values Ci. Given a finite abstraction of the program.e. Ck. We consider a language with abstract values C1.e. Ù. or Boolean combinations of constraints. i. in the remainder of this paper. Ck. which is precise with respect to the initial abstraction but contains choice variables. Conversely. . Ú. the equation describes the function f that always returns C1. After ensuring that satisfiability and validity are preserved under syntactic substitution. but only formulas that preserve satisfiability (for may queries) or validity (for must queries). Thus. We demonstrate experimentally that the resulting bracketing constraints are small in practice and. if a formula representing the condition under which the bad event happens is satisfiable. static analyses operate on a model or abstraction of the program rather than the program itself. or any chosen finite domain. . the constraints generated by the analysis are polymorphic. conditional expressions. typestates. which are by convention taken to have a nondeterministic value chosen on function invocation. if there are only two abstract values C1 and C2. for example. we usually index the corresponding constraint variable Pf. then the program may violate the desired property.May questions can be formulated as satisfiability queries. More formally. These abstract values can be any fixed set of predicates. we then solve the two recursive systems via standard fixedpoint computation.
  . i figure 1. C . and 12 implicitly quantify over multiple hypotheses. the abstract value of variable x is represented by constraint variable a. Then is the equation computed by the inference rules. and ⊥. then x has abstract value Ci only if a = Ci.1. describing the constraints F under which Note that rules 3. capturing that a function call returns only one value. where Ù is meet. As outlined in Section 1. 2. b in the constraint language. 53 | no. Rules 1–5 prove judgments A b e : F where b Î {true. the meaning of a system of equations E is a standard limit of a series of approximations q (E0). We briefly sketch the semantics of constraints. false £ . and ¬⊥ = ⊥. ¬true = false. false. true. constraints from Definition 1 can be encoded using Boolean logic. Our goal is to generate constraints characterizing the condition under which a given function returns an abstract value Ci. We Note that b is shared by the two constraints. Figure 1 presents most of the constraint inference rules for the language given above. Rule 8 says that if under environment A. false}. C [Ck/a]. Note that the substitution [C1/a] in the formula expresses that the argument of the recursive call to f is C1. q (E1). 11. In Rule 3. the algorithm has four major steps: • Eliminate choice variables by extracting strongest necessary and weakest sufficient conditions • Rewrite the equations to preserve satisfiability/validity under substitution • Eliminate recursion by a fixed point computation • Finally. giving the (possibly) mutually recursive conditions under which a function returns each abstract value.a. Example 1. an environment A maps program variables to variables a. in the greatest fixed point) represents nontermination of the analyzed program. in any solution b must be either C1 or C2. generated by repeatedly unfolding E. Ú is join. The value ⊥ in the least fixed point semantics (resp. Rules 6–11 prove judgments A Ci e : F that give the constraint under which expression e evaluates to Ci. Suppose we analyze the following function: define f(x) = if ((x = C1) Ú (Y = C2)) then C1 else f(C1) where y models an environment choice and the only abstract values are C1 and C2.research highlights an expression e evaluates to true or false in environment A. In these inference rules. Finally. 10. . then f (e) evaluates to i Ci under the constraint Fk Ù Pf. Constraints are interpreted over the standard four-point lattice with ⊥ £ true. rule 12 constructs systems of equations. We are interested in both the least fixed point (where the first approximation of all P variables is ⊥) and greatest fixed point (where the first approximation is ) semantics. inference rules. 8 . b 118 com municaTio nS o f T h e ac m | auGust 2 0 10 | Vol. two expressions e1 and e2 are equal whenever both have the same abstract value. . Given an assignment q for the choice variables b. and thus our target decision procedure for the last step is Boolean SAT. ¬ = . Reduction to Boolean constraints Our main technical result is a sound and complete method for answering satisfiability (may) and validity (must) queries for the constraints of Definition 1.a. and ¬ false = true. apply a decision procedure to the closed-form equations Because our abstraction is finite. Rule 11 presents the rule for function calls: If the input to function f has the abstract value Ck under constraint Fk. and the constraint under which f returns Ci is Pf. we have omitted explicit quantifiers to avoid cluttering the rules.b We briefly explain a subset of the rules in more detail. in particular. the remaining rules are omitted for lack of space but are all straightforward analogs of the rules shown.
  j = Ci Ù j = Cj is unsatisfiable for any i. AU g U ST 2 0 1 0 | VO l. More interestingly. sufficient) conditions should be as strong (resp. false} and the f’s 1 1 k n are quantifier-free formulas over Observe that any solution to the constraints generated according to the rules from Figure 1 must assign exactly one abstract value to each variable. the constraints from Figure 1 result in a recursive system of Boolean constraints of the following form: System of Equations 1. j such that i ¹ j. The / additional restriction V − (⎡f⎤) = 0 enforces that the strongest necessary condition for a formula f has no choice variables. we use V + (f) to denote the set of observable variables in f. Analogously. STRonGeST neceSSaRy anD WeakeST SufficienT conDiTionS As discussed in previous sections. and V − (f) to denote the set of choice variables in f. jin such that jij is true if and only if ji = Cj. otherwise. sufficient) conditions should be satisfiable (resp. a. C . we perform this translation first. Hence. weak) as possible. in the Boolean encoding ji Ù jj and ¬i ji are both still satisfiable. in the original semantics. . valid). We replace every substitution [Cj /ai] by the Boolean substitution [true/aij] and [false/aik] for j k. ((f Þ f¢ ) Þ (⎡f⎤ Þ f¢ )) (2) "f¢ / where V − (f¢ ) = 0 Ù V + (f¢ ) Í V + (f) The first condition says ⎡f⎤ is necessary for f. then the strongest necessary and weakest sufficient conditions of f are equivalent to f. C represents the condition under which f returns Ci. If f has only observable variables. valid) if and only if E is satisfiable (resp. C ’s as return variables. Let f be a quantifier-free formula. In the following. • The necessary/sufficient conditions should be only over observable variables. Since ⎡f⎤ is a necessary condition for f. i hence we refer to Pf. A variable i Pf. 8 | c om m u n ic aT ion S of T h e acm Note that subexpressions of the form ji = jj never appear in the constraints generated by the system of Figure 1.. and the second condition ensures ⎡f⎤ is stronger than any other necessary condition with respect to f’s observable variables V + (f). then the best possible bounds are ⎡f⎤ = true and ⎣f⎦ = false. . . in particular. We map the equation variables Pf. If f has only choice variables and f is not equivalent to true or false. C to Boolean variables of the same name. a. however. Definition 3. because ⎡f⎤ is the strongest such necessary condition. Let f be a quantifier-free formula. We say ⎣f⎦ is the weakest observable sufficient condition for f if: / (1) ⎣f⎦ Þ f (V − ( ⎣f⎦ ) = 0) (2) "f¢ . a key step in our algorithm 119 . b}) in the constraint language. we introduce Boolean variables ji1. before performing any of the steps above. Intuitively. and i j = Ci is valid. to encode these implicit uniqueness and existence axioms of the original constraints. C ñ and bi Î {true. we define satisfiability and validity in the following modified way: where fexist and funique are defined as: 3. . We also transi late each s1 = s2 occurring in the constraints as: is extracting necessary/sufficient conditions from a system of constraints E. The first row of Example 1 results in the following Boolean constraints (here Boolean variable a1 represents the equation a = C1 and b2 represents b = C2): In the general case. This section makes precise exactly what necessary/sufficient conditions we need. 53 | N O. Pf . ((f¢ Þ f) Þ (f¢ Þ ⎣f⎦ )) / where V − (f¢ ) = 0 Ù V + (f¢ ) Í V + (f ) Let f be the condition under which some program property P holds. . by virtue of ⎡f⎤ being a strongest necessary condition. . a. One can think of strongest necessary and weakest sufficient conditions of f as defining a tight observable bound on f. Then. a. a. the satisfiability of f implies the satisfiability of ⎡f⎤. there are two technical requirements: • The necessary (resp.must at some point translate the constraints from Figure 1 into equivalent Boolean constraints. We say ⎡f⎤ is the strongest observable necessary condition for f if: / (1) f Þ ⎡f⎤ (V − ( ⎡f⎤ ) = 0) . the satisfiability of ⎡f⎤ also implies the satisfiability of f. We now continue with an informal example illustrating the usefulness of strongest observable necessary and weakest sufficient conditions for statically analyzing programs. Definition 2. a stronger necessary condition would be false. querying the satisfiability of ⎡f⎤ is equivalent to querying the satisfiability of the original constraint f for deciding if property P may hold. Example 2. More specifically. querying the validity of ⎣f⎦ is equivalent to querying the validity of the original constraint f for deciding if property P must hold. the “difference” between strongest necessary and weakest sufficient conditions defines the amount of unknown information present in the original formula. For every variable j (j Î{a. The necessary (resp. where = áPf ..
  5.3). 4. let b be a choice variable to be eliminated. a. example code. Observe that these strongest necessary and weakest sufficient conditions are as precise as the original formula for deciding whether p is dereferenced by f at any call site of f. Consider the implementation of f given in Figure 2. we solve the equations to eliminate recursive constraints (Section 4. The existence and uniquencess constraints are 1 omitted since they are redundant. and furthermore. the weakest observable sufficient condition for the dereference is false. a. we use the following well-known result for computing strongest necessary and weakest sufficient conditions for Boolean formulas4: Lemma 1. Each step preserves the satisfiability/validity of the original equations. We compute the weakest sufficient condition for Pf. respectively. Preservation under substitution Our goal is to solve the recursive system given in System of Equations 2 by an iterative. 1. System of Equations 2 may not preserve strongest necessary and weakest sufficient conditions under substitution for two reasons: • Strongest necessary and weakest sufficient conditions are not preserved under negation (i.. In particular. and let ψexist and ψunique represent the existence and uniqueness conditions involving b. 8. The strongest necessary and weakest sufficient conditions of Boolean formula f not containing variable b are given by: SNC (f. SoLVinG The conSTRainTS In this section. b) º f[true/b ] Ù f[false/b ] After applying these elimination procedures to the constraint system from Figure 1.. *buf = getUserInput(). f . • The formulas from System of Equations 2 may contain contradictions and tautologies involving return variables. ESC is analogous to ENC. *p = 1. Ø⎡f⎤ ⎡Øf⎤ and Ø⎣f⎦ ⎣Øf⎦ ). fixed point computation. Finally. We then manipulate the system to preserve strongest necessary (weakest sufficient) conditions under substitution (Section 4. 6. C is true. 8 . these formulas are much more concise than the original formula. Then. Therefore.2. Cj from System i of Equations 1. It is easy to see that the exact condition for p’s dereference is given by the constraint: p!=NULL Ù flag!=0 Ù buf!=NULL Ù *buf ==’i’ Since the return value of malloc (i. substituting ØP by Ø⎡P⎤ and Ø⎣P⎦ would yield incorrect necessary and sufficient conditions.2). } Example 3. C : 1 The reader can verify that the strongest necessary condition for Pf. 3.. we obtain two distinct sets of equations of the form: System of Equations 2. and thus the original may/must query can be decided using a standard SAT solver on the final formulas. this standard way of computing strongest necessary and weakest sufficient conditions of Boolean formulas must be slightly modified. However.1. the strongest observable necessary condition for f to dereference p is given by the simpler condition: p!=NULL Ù flag!=0 On the other hand. we compute strongest necessary and weakest sufficient conditions as follows: figure 2. Our algorithm first eliminates the choice variables from every formula. void f(int* p. if(!buf) return. if(!p || !flag) return. if(*buf==’i’) 7. char* buf = malloc(sizeof(char)). there is a problem: as it stands. causing the formula to be weakened (for neces- 120 comm unicaTio nS o f Th e ac m | auG ust 2 0 10 | Vol. Consider the function given in Example 1. we now return to the problem of computing strongest necessary and weakest sufficient conditions containing only observable variables for each Pa. 4. int flag) { 2. buf) and the user input (i. which makes sense because no restriction on the arguments to f can guarantee that p is dereferenced.e. for which Boolean constraints are given in Example 2. *buf) are statically unknown. Example 4.research highlights Since our definition of satisfiability and validity must also take into account the implicit existence and uniqueness conditions.e. and the formulas from System of Equations 2 contain negated return (P) variables.e. 53 | no. 4. yielding a system of (nonrecursive) formulas over observable variables. 4. and suppose we want to determine the condition under which pointer p is dereferenced in f. b) º f[true/b ] Ú f[false/b ] WSC (f. eliminating choice variables To eliminate the choice variables from the formulas in Figure 1.
  While it is important in our technique that the set of possible values can be exhaustively enumerated (to guarantee the convergence of the fixed point computation and to be able to convert the constraints to Boolean logic). In the first set of experiments we compute necessary and sufficient AU g U ST 2 0 1 0 | VO l. This rewrite explicitly enforces any contradictions and tautologies present in the original formula such that substituting the P variables with their necessary (resp. This results in a system of bracketing constraints of the form: System of Equations 3. a. reads from unbounded data structures. C . Furthermore. For the first problem. by simultaneously computing strongest necessary and weakest sufficient conditions. true. This means 121 . To compute a least fixed point. Hence. if one is interested in combining reasoning about two distinct properties. the formula may be converted to conjunctive normal form and tautologies can be removed. C û for 1 the function f defined in Example 1 as: ëPf. but only finitary. In particular. sources of imprecision in the analysis appear as nondeterministic choices. 53 | N O. imprecise loop invariants. the following equivalences do hold: ⎡Øf⎤ Û Ø⎣f⎦ ⎣Øf⎦ Û Ø⎡f⎤ In other words. a. it is necessary to compute strongest necessary and weakest sufficient conditions for the combined property. finite for a given program. As a result. and similarly. we use the following lattice: that in some cases involving nonterminating program paths. eXPeRimenTaL ReSuLTS We have implemented our method in Saturn. it is possible to obtain a closed form solution containing only observable variables to System of Equations 2 using a standard fixed point computation technique. arithmetic. the proposed technique is not complete for arbitrary nonfinite domains. eliminating recursion Since we now have a way of preserving strongest necessary and weakest sufficient conditions under substitution. 4. but the algorithm presented in this paper may return either true or false. C û. for weakest sufficient conditions. 8 | c om m u n ic aT ion S of T h e acm The lattice L is finite (up to logical equivalence) since there are only a finite number of variables aij and hence only a finite number of logically distinct formulas. and in-line assembly. Similarly. our results are qualified by the assumption that the program terminates. LimiTaTionS While the technique proposed in this paper yields the strongest necessary and weakest sufficient conditions for a property P with respect to a finite abstraction. sufficient) conditions cannot weaken (resp. 6. namely ^. Fortunately. 1 a tautology. if f1 and f2 are the strongest necessary conditions for P1 and P2 respectively. it is not precise for separately tracking the conditions for two distinct properties P1 and P2 and then combining the individual results. a static analysis framework designed for checking properties of C programs. Hence. sources of imprecision include. all of these sources of imprecision in the analysis are treated as choice variables. in Saturn. one can solve the first problem using the above equivalences. as weak) as possible.1 As mentioned in Section 1. it can also be extended to any property where a finite number of equivalence classes can be derived to describe the possible outcomes. observe that while Ø⎡f⎤ ⎡Øf⎤ and Ø⎣f⎦ ⎣Øf⎦ . false. an obvious solution is to convert the formula to disjunctive normal form and drop contradictions before applying a substitution in the case of strongest necessary conditions. the strongest necessary condition of Øf is the negation of the weakest sufficient condition of f. 1 Since f is always guaranteed to return C1. Example 5. the weakest sufficient condition of Øf is the negation of the strongest necessary condition of f. we first 1 substitute true for ëPf. while the resulting closed-form strong necessary and weakest sufficient conditions evaluate to either true or false. and . Recall that in Example 4 we computed ëPf. the obtained necessary (resp. 5. a. the original system of equations may have meaning ^ in least fixed-point semantics (or in greatest fixed-point semantics). We conducted two sets of experiments to evaluate our technique on OpenSSH.3. both of these problems can be remedied. and weakest sufficient conditions do not distribute over disjunctions. then f1 Ù f2 does not yield the strongest necessary condition for P1 and P2 to hold together because strongest necessary conditions do not distribute over conjunctions. Samba. strengthen) the solution. depending on whether a greatest or least fixed point is computed. This yields the formula a1 Ú Øa1. C û [true/a1]) 1 1 To find the weakest sufficient condition for Pf. that is. it is not necessary that the set be finite. As a result.sary conditions) and strengthened (for sufficient conditions) as a result of substituting the return variables with their respective necessary and sufficient conditions. Hence. our algorithm finds the fixed point solution true for the weakest sufficient condition of Pf. C û = a1 Ú (Øa1 Ù ëPf. imprecise function pointer targets. C . However. To overcome the second problem. the weakest sufficient condition computed using our algorithm is the most precise solution possible. sufficient) conditions may not be as strong (resp. Recall from Section 2 that the original constraints have four possible meanings. and the Linux kernel. a. a. but are not limited to. while it is clear that the technique can be applied to finite-state properties or enumerated types. a.
  red bars indicate necessary conditions. In Figure 2.6.000 figure 5. for each function. Figure 4 presents average necessary and sufficient condition sizes at sinks (rows 2 and 3) for all three applications we analyzed.1 The first three columns of Figure 5 give the results of the experiments for the first setup. /*source*/ .02 0. but we do not track the condition under which pointers are dereferenced across functions. int flag.6. we only compute which pointers may be dereferenced in that function.23b 1. and note that the y-axis is drawn on a log-scale.000 Necessary Condition Sufficient Condition 10. the necessary condition at p’s source for p to be ultimately dereferenced is x > MAX Ú (x <= MAX Ù p! = NULL Ù flag! = 0)and the sufficient condition is x > MAX. consider the following call site of function f from Figure 2: The line marked /*source*/ is the source of pointer p. For the sink experiments. confirming that average necessary and sufficient condition sizes are consistently small across all of our benchmarks.2 to bug ratio 100 10 1 0–4 5–9 10–14 15–19 20–24 25–29 30–34 35–39 40–44 Size of necessary and sufficient conditions 122 co m municaT io nS o f T h e acm | auG ust 2 0 10 | Vol..e. we use the technique described in the paper. where pointers are dereferenced. compute the necessary and sufficient conditions for p’s dereference as p! = NULL Ù flag!=0 and false respectively.0.0. frequency of necessary and sufficient condition sizes (in terms of the number of Boolean connectives) at sinks for Linux. the intraprocedurally path-sensitive case). we incorporate our technique into a null dereference analysis and demonstrate that our technique reduces the number of false positives by close to an order of magnitude without resorting to ad-hoc heuristics or compromising soundness.000 Frequency (in log scale) Average NC size (sink) Average SC size (sink) Average NC size (source) Average SC size (source) Average call chain depth lines of code 1. Observe that 95% of all necessary and sufficient conditions have fewer than five subclauses.. without the elimination of choice variables. (i) the interprocedurally path-sensitive analysis may not even terminate.45 5. sufficient) conditions against the number of constraints that have a necessary (resp. necessary and sufficient condition sizes (in terms of number of Boolean connectives in the formula) for pointer dereferences. The results of the sink experiments for Linux are presented in Figure 3.3p2 3.17.75 0. sufficient) condition of the given size.98 6. for this reason. int x) { if(x > MAX) *p = −1. green bars indicate sufficient conditions. Samba.23b 2. } pointers are first allocated or read from the heap.017 Samba 3. In our first set of experiments. To illustrate the source experiment.03 155.67 2.67 515. and 99% have fewer than ten subclauses. for example. linux 2. 53 | no.1 Total reports 3 48 171 21 379 1495 bugs 1 17 134 1 17 134 False positives 2 25 37 20 356 1344 Undecided 0 6 17 0 6 17 report 3 2. Interprocedurally Intraprocedurally Path-Sensitive Path-Sensitive OpenSSH Samba linux OpenSSH Samba linux 4.research highlights conditions for pointer dereferences.1 0. and at sources. 8 .689 OpenSSH 4. In fact.275.23b 2. Results of null dereference experiments. flag). In this figure.1 4.17.39 0. all previous analyses written in Saturn were either interprocedurally path-insensitive or adopted incomplete heuristics to decide which conditions to track across function boundaries.6. we compare two different setups: In the interprocedurally path-sensitive analysis. } void bar(int* p. Pointer dereferences are ubiquitous in C programs and computing the necessary and sufficient conditions for each and every syntactic pointer dereference to execute is a good stress test for our approach. In the results presented in Figure 5.660 Necessary and sufficient condition size frequency 100. flag.3p2 0. where void foo() { int* p = malloc(sizeof(int) ). We believe this comparison is useful in quantifying the benefit of the technique proposed in the paper because. We chose null dereferences as an application because checking for null dereference errors with sufficient precision often requires tracking complex path conditions. The histogram in Figure 3 plots the size of necessary (resp. and Linux.48 2. overwhelming the constraint solver. figure 3.17.50 1. The table in Figure 4 presents a summary of the results of both the source and sink experiments for OpenSSH.67 2. and (ii) the number of choice variables grows linearly in the size of the program.0. bar(p.. we would.49 4.3 11.82 0. and the last three columns of the same figure present the results of the second figure 4. As a second experiment. x).8 1. consider the pointer dereference (sink) at line 7. showing that necessary and sufficient conditions are small in practice.75 0. we measure the size of necessary and sufficient conditions for pointer dereferences both at sinks. else f(p. computing strongest necessary conditions for a null pointer to be dereferenced.39 0. In the second setup (i.3p2 3. Our second experiment applies these techniques to finding null dereference errors.3 21 22.
  Foundation.. the award-winning nonproﬁt e-mentoring network in engineering. In International Symposium on Programming (1984). NVIDIA. automatically validating temporal safety properties of interfaces. 1858. and The Henry Luce Foundation.mentornet. G. Share what you’ve learned. Naval Research Laboratory. esP: Path-sensitive program verification in polynomial time. boole. 5. LNCS 2057 (2001). An Investigation of the Laws of Thought. Saturn does not have a sophisticated shape analysis. MentorNet’s award-winning One-on-One Mentoring Programs pair ACM student members with mentors from industry.net Find out more at:. a.. the overwhelming majority (>95%) of errors reported for elements of unbounded data structures are false positives..setup. das. AU g U ST 2 0 1 0 | VO l. s. We argued that. Bechtel Group Foundation.. Horwitz. Note that the existence of false positives does not contradict our previous claim that our technique is complete. Incorporated. sagiv. 9.. 7. t. Vardi. rajamani.. 217–228. Polymorphic type schemes and recursive definitions. t. dillig. bugrara. and other sectors. b. and Alex Aiken {isil. 6. Cisco Systems. Jr.. • Communicate by email about career goals. ACM has partnered with MentorNet. In POPL (2004). bebop: a symbolic model checker for boolean programs. Isil Dillig. r. 8 | c om m u n ic aT ion S of T h e acm 123 . rybalchenko. • Take part in a lively online community of professionals and students all over the world. Jhala. government. hence.. Sandia National Laboratories. Texas Instruments.. tdillig. s. b.00 You’ve come a long way. s. 1 (2007). A comparison of the results of the intraprocedurally and interprocedurally path-sensitive analyses shows that our technique reduces the number of false positives by close to an order of magnitude without resorting to heuristics or compromising soundness in order to eliminate errors arising from interprocedural dependencies. Science of Computer Programming 64. our technique can provide only relative completeness. science and mathematics. 11.. 29–53. course work. aiken. 53 | N O. 10. t. ball. M. Sign up today at: www. References 1. Hackett. P.. One important caveat is that the numbers reported here exclude error reports arising from array elements and recursive fields of data structures. shape analysis is an orthogonal problem which we neither address nor evaluate in this work. Gotsman. National Science Foundation. In PASTE (2007).. a. S. Cook. In POPL (2007). 43–48. concLuSion We have presented a method for systematically reasoning about unknown values in static analysis systems.. reps. abstractions from proofs. Hawkins. higher education. ACM. Schlumberger. Intel Foundation. a. 2. Henglein. 49–61. we cannot guarantee completeness for arbitrary domains. 57–68. We have presented a technique to eliminate these choice variables with no loss of information for answering may and must queries about program properties. • Spend just 20 minutes a week . schmidt. M. 3. 8. In PLDI (2002). F.and make a huge diﬀerence in a student’s life. Make a diﬀerence to a student in your ﬁeld. a calculus of logical relations for over-and underapproximating static analyses. eliminating these choice variables at function boundaries is necessary to avoid both scalability as well as termination problems. 4. In SPIN (2000). r. 265–276... However. aiken}@cs. a. 232–244. Bechtel. rajamani. Precise interprocedural dataflow analysis via graph reachability.org/mentornet MentorNet’s sponsors include 3M Foundation. 184–197. while our results are complete for finite domains. a. First. M. t. Alcoa Foundation. Podelski. Mycroft. even for finite domains. seigle. In POPL (1995). false positives can still arise from orthogonal sources of imprecision in the analysis. Lockheed Martin Space Systems. M. dover Publications. 113–130. d. Agilent Technologies. Computer science department. We have also experimentally demonstrated that analyzing unknown values in this way leads to much better precision and better scalability. Proving that programs eventually do something good. Hewlett-Packard Company. s..stanford. 103–122. ball. t. type inference and semi-unification. 7. s. lerner..D.edu. © 2010 aCM 0001-0782/10/0800 $10. Amylin Pharmaceuticals. K. IBM Corporation. dillig. I. McMillan. Henzinger. an overview of the saturn project. and many other topics. stanford university. Thomas Dillig. while representing unknown values by choice variables adds useful precision by correlating multiple uses of the same unknown value. Second. Majumdar. In Conference on LISP and Functional Programming (1988).
  an e-Reference Library extends technical knowledge outside of the classroom. in ACM’s rotating collection of complete unabridged books on the hottest computing topics. Available to ACM Professional Members. Reference Tools . Your bookshelf allows for quick retrieval and bookmarks let you easily return to specific places in a book.org www. without a live Internet connection.round-the-clock access to 3. right when you need it.members can access assessments and self-study courses oﬄine. 500 Online Books from Books24x7 All Professional and Student Members also have full access to 500 online books from Books24x7®. For more details visit: unique vLab® exercises place users on systems using real hardware and software allowing them to gain important job-related experience.org/join . The ACM Online Course Program is open to ACM Professional and Student Members. pd. or read cover-to-cover. 1. anywhere and anytime.200 Online Courses in Multiple Languages Plus 1.000 virtual labs. in multiple languages. bookmark.CACM_ACM_Books_and_Courses_4C_full-page_LMNTK:Layout 1 6/29/10 3:48 PM Page 1 ACM’s Online Books & Courses Programs! Helping Members Meet Today’s Career Challenges NEW! 3.000 Virtual Labs from Element K! ACM’s new Online Course Collection includes over 3. Safari will help you zero in on exactly the information you need. and oﬄine capability.200 online courses on a wide range of computing and business topics. This virtual library puts information at your fingertips. Oﬄine Player . e-reference tools. Safari puts a complete IT and business e-reference library right on your desktop. A downloadable Quick Reference Guide and a 15-minute site orientation course for new users are also available to help members get started.1. Search.200 online courses in multiple languages.org/books/about_sel.acm. featuring leading publishers including O’Reilly. plus online Executive Summaries and quick reference cards to answer on-the-job questions instantly.acm. 600 Online Books from Safari ACM members are eligible for a special 40% savings oﬀer to upgrade to a Premium or Full Library subscription. Exclusive vLab® Virtual Labs .cfm The ACM Online Books Collection includes full access to 600 online books from Safari® Books Online. Program highlights: The ACM E-Learning Catalog .acm.
  D. and treatment of human disease with research in one or more of the following areas: biomedical models. and proven leadership and team building skills. in the Upper Valley region of New Hampshire.D. Applicants are invited to send their CV. 53 | N O. Inc. requirements and application process. 2010. and social Anthropology. The Neukom Institute for Computational Science (. statement of teaching and research interests. The closing date for applications is August 25. Duties include undergraduate and graduate teaching and development of a strong. Bradley University is an EEO/AA employer. The Institute has considerable financial and computing resources that will be available to the successful candidate./Ph. program. especially the African Canadian community. It is a beautiful. vision/graphics. machine learning. Johnston Chair in Black Canadian Studies Dalhousie University invites applications for the James R.500 students and 12 Faculties. this position is restricted to candidates with an African (Black) heritage. We seek candidates in the area of computational biology and bioinformatics whose research focuses on the development and application of new computational methods. and is being recruited to one of the following three faculties: Faculty of Science (Psychology). and Mathematics. Katherine Rudolph Office of the Vice-President Academic and Provost Room 108. dynamic traffic assignment. Nuance Communications. located in a scenic. Dalhousie university James R. The Department of Computer Science (www. Dartmouth is an equal opportunity/affirmative action employer and encourages applications from women and members of minority groups.dartmouth. and convenient public transportation to Boston and New York. The candidate will have demonstrated abilities in collaborative research with African Canadian communities.Bernard@dal. Employment Specialist. rehabilitation engineering. and systems. as well as local airports. Henry Hicks Academic Administration Building Dalhousie University 6299 South Street Halifax. field & 2 yrs. 2010. Senior Software Engineer Senior Software Engineer wanted to develop speech recognition software for OEM-based mobility handsets. The successful applicant will have expertise and experience in core modeling and simulation (M&S) areas and a commitment to quality teaching in the department’s bachelors. Tenure-track Faculty Position The Neukom Institute for Computational Science and the Department of Computer Science at Dartmouth College invite applications for a tenuretrack faculty position at the level of Assistant Professor in the Department of Computer Science. and names old Dominion university Modeling and Simulation Faculty Positions The Department of Modeling. This will be Dalhousie’s third appointment to the James R. Applicants must have a Ph. renowned musical and theatrical performers. Must have Master’s deg. This is an opportunity to join and help shape the first M&S department. Located in Halifax. Dalhousie is one of Canada’s top teaching and research universities and is the largest university in Atlantic Canada with approximately 15. software programming or engineering involving C/C++ programming & debugging & incl.bradley. The positions require that a PhD in Computer Science or a closely related field be completed prior to start date. externally-funded research program. MA 01803-4613. computer science.” Halifax is the largest city in Atlantic Canada and affords its citizens an outstanding quality of life. Direct inquiries may be sent to Professor Hany Farid (farid@cs. 2011. however. to advance Black studies in the university and through the holder of the Endowed Chair to establish better links with the wider community. Dartmouth is an Ivy League school situated in Hanover. the endowed chair is a tenured. historic campus. multimodal logistics. The department has strong Ph. Nova Scotia B3H 4H6 Canada Katherine.. Sc. and three letters of reference. and is affiliated with an M. (2) M&S for transportation system operation and planning with research in one or more of the following areas: network modeling. statement of teaching and research interests.edu). Burlington. Must have strong interpersonal skills for dealing directly with customers both verbally & in writing. and M. and telemedicine. outstanding undergraduate majors and minors. medical training devices and systems. Must have strong proficiency in C language. The successful candidate for the Chair will be an outstanding scholar of African descent with a doctoral degree in her/his discipline. Simulation and Visualization Engineering at Old Dominion University’s Batten College of Engineering and Technology invites applications for two tenure-track faculty positions beginning January 2011. medical robotics. flow optimization. The candidate will also have established links with the local and/or national African Canadian communities. and a clear track record of nationally and internationally recognized research in their field. and three confidential letters of reference forwarded under separate cover by the referees should be submitted to: Dartmouth college Computer Science Dept. Dartmouth hosts an annual film festival. Johnston chair in Black canadian studies from outstanding scholars in the fields of psychology. programs. senior academic position. in Comp.edu/~neukom) is an endowed institute whose broad mandate is to inspire and support computational science across the Dartmouth campus. For full position description. research statement. supply chain management. nuance communications.edu by September 1st. and doctoral programs. Applications should include a cover letter. it is known for the range and excellence of its teaching programs and is recognized as “the research powerhouse of Atlantic Canada. Johnston Chair in Black Canadian Studies. as well as the Dartmouth Medical School.edu) is home to 17 tenured and tenure-track faculty whose research spans computational biology. Canadians and permanent residents will be given priority. All qualified candidates are encouraged to apply. Established in 1818. Applications. as demonstrated through employer screening test. This Endowed Chair was established by Dalhousie University to contribute to the field of Black Canadian Studies. Candidates will complement a growing program in computational biology within the Departments of Biology. Computer Science.. algorithms. For more information about Dalhousie University and/or the James R.cs.ca The appointment is effective July 1.dartmouth. Johnston Chair. All application materials must be submitted via email as a single pdf document to Dr. Engineering or rel. including a CV. Roland 125 AU g U ST 2 0 1 0 | VO l.D. theory. of at least four references.edu/humanresources/opportunities. outdoor recreational area. All material should be sent to search@cs. 8 | c om m u n ic aT ion S of T h e acm . please contact: Wanda. complete resume.D. one of whom should comment about teaching. Faculty of Computer Science. masters. and real-time control of transportation systems.. on the Connecticut River. in an engineering or science discipline closely related to M&S. Send resume to Melissa Cornell. Preference will be given to applicants having experience in performing interdisciplinary research in: (1) M&S for detection. We are seeking a senior candidate with previous teaching experience. One Wayside Rd.Rudolph@dal.S. visit www. embedded software development. teaching statement. or Faculty of Arts and Social Sciences (Social Anthropology).CAREERS Bradley university Assistant Professor The CS&IS Department invites applications for two tenure track Assistant Professor positions beginning August 2011.dartmouth. education. Engineering Sciences.ca In keeping with Dalhousie University’s Employment Equity/Affirmative Action Policy. year-round. inc.
  or sent via postal mail. at the following email address: rmayo@odu. ford University. Master’s. The appointed will be expected to do innovative research in the OIT field.edu. 5 3 | NO. teaching and clinical missions. and/or statistical modeling methodologies. all materials may be sent by e-mail to Faculty_Recruiter@GSB. starting in the 2011-2012 academic year.edu. Bachelor’s degrees and Higher Diploma levels.htm 126 co m municaTio nS o f T h e acm | AU gU ST 201 0 | VO l .polyu. each applicant must have three letters of recommendation emailed to the preceding email address. Stan- Texas a&m university Department of Computer Science and Engineering Department Head The Dwight Look College of Engineering at Texas A&M University invites nominations and applica- The Hong Kong Polytechnic University is the largest government-funded tertiary institution in Hong Kong in terms of student number. in which technology. Stanford. Alternatively. The University is now inviting applications and nominations for the following post: Head of Department of Computing Please visit the following websites for more information: The Hong Kong Polytechnic University:. Applicants are expected to have rigorous training in management science. The total consolidated expenditure budget of the University is in excess of HK$4 billion per year. if applicable. on that site. Graduate School of Business. Chair. Stanford. It welcomes nominations of and applications from women and minority groups. All ranks and relevant disciplines will be considered. and teaching evaluations. MSVE Department. It has a full-time academic staff strength of around 1. Box OIT. Review of applications will begin September 1. economics. 2010 and will continue until the positions are filled. However. as well as others who would bring additional dimensions to the University’s research. Applicants are strongly encouraged to submit their applications electronically by visiting the web site. CA 94305-5015. people. engineering. 2010. It offers programmes at Doctorate.hk/hro/job_external. to participate in the school’s PhD program and to teach both required and elective courses in the MBA program. and markets interact. Information and Technology (OIT) that are broadly defined to include the analytical and empirical study of technological systems. 8 . and management of technology.edu. the application deadline is november 15.stanford. Junior applicants should have or expect to complete a PhD by September 1. It thus includes operations. information systems/technology.edu/recruiting and uploading their curriculum vitae. tenure-track positions.400. or by postal mail (non-returnable) to Office of Faculty Recruiting.hk/ More information on the above post:. 518 Memorial Way. is seeking qualified applicants for full-time. Old Dominion University is an equal opportunity. computer science. submissions via e-mail and postal mail can take 4-6 weeks for processing. Stanford University. affirmative action institution and requires compliance with the Immigration Reform and Control Act of 1986. Stanford university Graduate School of Business Faculty Positions in Operations.Edu. For an application to be considered complete. research papers and publications.CAreerS Mielke. and Technology The Operations. Applicants are considered in all areas of Operations.gsb. Stanford University is an equal opportunity employer and is committed to increasing the diversity of its faculty. 2011. Information and Technology (OIT) area at the Graduate School of Business.polyu. Information.
  edu.org. The minimum is six lines. The Penn CIS Faculty is sensitive to “two-body problems” and would be pleased to assist with opportunities in the Philadelphia region. faculty and staff from diverse backgrounds.upenn. and indicate the issue/or issues where the ad will appear.org/publications career opportunities online: classified and recruitment display ads receive a free duplicate listing on our website at:. age. and currently has over 10. a full curriculum vitae. Candidates should possess proven leadership and administrative skills. Applicants should hold a graduate degree (preferably a Ph. and one ACM Distinguished Scientist. We are looking for an innovative thinker with a strategic vision for guiding the Department to a higher level of excellence who can communicate this vision to a constituency that includes academia. applications are due by september 15. excellence in teaching undergraduate courses.tions for the position of Head of the Department of Computer Science and Engineering.edu).S. seven IEEE Fellows. a land-grant. for more information contact: acm media Sales at 212-626-0654 or acmmediasales@acm.cis. Duties for the first Lecturer position include advanced computer graphics courses within two programs: the Bachelor of Science and Engineering in Digital Media Design. Deadlines: five weeks prior to the publication date of the issue (which is the first of every month). Applications will be accepted until the position is filled. and alumni.org AU g U ST 2 0 1 0 | VO l. More information is available at http:// www. Texas A&M. estimates: an insertion order will then be e-mailed back to you. The Department offers B. Please include text. government. degrees in computer science and. The University of Pennsylvania values diversity and seeks talented students. disability. 2011. and a contact name and number. university of Pennsylvania Department of Computer and Information Science Lecturer The University of Pennsylvania’s Department of Computer and Information Science invites applicants for two Lecturer positions. 2. The position starts January 1. and Ph. Lecturer positions are for one year. or other University administered programs or employment. industry. It now has 38 tenured and tenure-track faculty members and four full-time lecturers.tamu. its graduate computer engineering program was ranked #13 and its graduate computer science #27 in the recent US News and World report ranking of public institutions.shtml Electronic applications are strongly preferred. PA 19104-6389 Applications should be received by each date listed above to be assured full consideration. Duties for the second Lecturer position include introductory programming courses for majors and non-majors. the Department is expected to add faculty positions at both the junior and senior level. renewable annually up to three years. screening will begin immediately. Applications will be accepted until positions are filled.000. Texas A&M University is an Equal Opportunity/ Affirmative Action Employer. The ad will by typeset according to cacm guidelines. two ACM Fellows. national or ethnic origin. gender identity. The Department is playing an active role in many campus-wide and System-wide initiatives. Master’s. classified line ads are noT commissionable. the names and addresses of at least five references.50 for each additional line after the first six.00 for six lines of text. The department seeks individuals with exceptional promise for. and it ranks among the top institutions in every significant national poll. and have a strong interest in teaching with practical application. In recent years. and other courses within the Computer Science program. scholarship and loan awards. The University of Pennsylvania does not discriminate on the basis of race. 2011. including editorships for scientific journals and general chairs of technical conferences.edu/departmental/ facultyRecruiting. It has long enjoyed national leadership status in engineering education. Successful applicants will find Penn to be a stimulating environment conducive to professional growth in both teaching and research.edu. but hard-copy applications (including the names of at least four references) may alternatively be sent to: Chair.acm.) in Computer Science or Computer Engineering. Today. the Department has built a strong national reputation based on the quality of its faculty and programs. including #8 for graduate programs and #9 for undergraduate programs in the recent US News and World report ranking of public institutions. color. Latest deadlines:. and an established reputation as a scholar consistent with an appointment to the rank of Professor of Computer Science and Engineering with tenure.upenn. In the next few years. to roughly 350 graduate and 600 undergraduate students. sex. Faculty Search Committee Department of Computer and Information Science School of Engineering and Applied Science University of Pennsylvania Philadelphia. 127 aDVeRTiSinG in caReeR oPPoRTuniTieS how to Submit a classified Line ad: Send an e-mail to acmmediasales@ acm. or status as a Vietnam Era Veteran or disabled veteran in the administration of educational policies.cse. $32. 40 characters per line. in computer engineering. The Department’s annual research budget for 2009 was $10.000. with research known throughout the international academic community and global industry alike.. Letters of application should include: 1. at the end of which a promotion to Senior Lecturer can be considered. one Association for the Advancement of Science Fellow. The faculty is also wellrecognized for contributions to their fields. The faculty holds over 60 important and influential professional positions.cis. religion. a two-page statement summarizing the candidate’s vision and goals for the Department and leadership philosophy.cis. programs or activities. the Dwight Look College of Engineering is one of the largest and best endowed in the nation.000 students. 53 | N O. is one of the six largest universities in the United States and has over 48. Women and minorities are encouraged to apply. and space-grant institution. jointly with the Department of Electrical and Computer Engineering.org/careercenter ads are listed for a period of 30 days. Questions can be addressed to : faculty-search@central. athletic. applications are due by January 15. 8 | c om m u n ic aT ion S of T h e acm . Employer paid advertisement. 2011. The Department currently has one National Academy of Engineering member. 2010.000 engineering students in twelve departments. sea-grant.D. To apply.acm.D.upenn. and the Master of Science and Engineering in Computer Graphics and Game Technology (see. sexual orientation. including in half of the eight multidisciplinary research directions identified in the recently completed University Academic Master Plan and in the newly established Energy Engineering Institute. Approximately 25 percent of the engineering students are graduate students. or a proven record of. admissions policies. no PRoofS can be sent. The Department of Computer Science and Engineering has recently gone through an expansion with the hiring of 21 faculty members in the past eight years. please complete the form located on the Faculty Recruitment Web Site at:. Rates: $325. The position starts July 1. and 3. Nominations or applications should be sent to csechair@tamu. 40 percent of the faculty are holders of NSF CAREER/NYI/PYI awards.
  nH. they are transparent so we can see them. They are not. Prove the sheet can be placed over the stain in such a way that no intersection point of the grid falls on the stain. 8 . We examine simple but intriguing questions about figures on the plane. in our briefcase is a large transparent sheet of plastic on which is printed a square grid of side one inch. even with a computer’s help. Erdo s. All readers are encouraged to submit prospective puzzles for future columns to puzzled@cacm. In each.last byte DOI:10. 2. The three coins at the bottom are not needed. Figure 1 shows a successful placement for a particular stain. Fejes Tóth… or anyone ˝ waiting impatiently for. On the table before us are 10 dots.acm. Meanwhile. the third is (as yet) unsolved. the issue is how your intuition matches up with the mathematics. Solutions to the first two will be published next month. 5 3 | NO. the kinds of questions one would find in Euclid’s Elements but more what could be expected from Minkowski. and in our pocket are 10 $1 coins. On the tablecloth before us in one such restaurant is a gravy stain of an area less than one square inch. What is the true maximum value of n? I guess around 25. food to be served in a restaurant.org) is Professor of Mathematics and of Computer science and albert bradley third Century Professor in the sciences at dartmouth College. 1.org. Prove the coins can be placed on the table (no two overlapping) in such a way that all dots are covered.1787260 Peter Winkler Puzzled figures on a Plane Welcome to three new puzzles.1145/1787234. Peter Winkler (puzzled@cacm. Figure 2 shows a valid placement of the coins for this particular set of dots. 3. 128 co m municaTio nS o f T h e acm | AU gU ST 201 0 | VO l . What is the largest number n such that any n points on the plane can be covered by disjoint unit disks (like the coins in the second puzzle)? That is. what is the largest number we can replace the 10s by in the second puzzle so it remains true? We know from the solution to the second puzzle that the maximum n is at least 10. but it might be quite difficult to pin it down. so n is less than 60. Your author can construct a pattern of 60 points (in a triangular lattice) that cannot be covered by disjoint unit disks. Hanover.acm. say. perhaps.
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  CNR-ISTI.3RD ACM SIGCHI SYMPOSIUM ON ENGINEERING INTERACTIVE COMPUTING SYSTEMS NOVEMBER 22. 2010 Submission deadline for Long Papers and Workshops FEBRUARY 10. Univ. CNR-ISTI. Tutorials LOCATION Area della Ricerca CNR Pisa.org PISA 2011 JUNE 13-16 EICS is sponsored by ACM SIGCHI . HIIS Laboratory LONG PAPER CHAIRS Kris Luyten.ORG CONFERENCE CHAIR Fabio Paternò. UNC Chapel Hill Carmen Santoro. of Hasselt Frank Maurer. Univ.EICS2011. 2011 Submission deadline for Late Breaking Results. Doctoral Consortium. Demos. ITALY More updated information at WWW. please contact info@eics2011. of Calgary Late Breaking Results CHAIRS Prasun Dewan. HIIS Laboratory For information.