text:
Book your room at Hipotel Marne la Vallée
Double RoomMax Occupancy: 2 guests (up to 1 child, 1 infant)
Triple RoomMax Occupancy: 3 guests (up to 2 children, 1 infant)
Single RoomMax Occupancy: 1 guest
Quadruple RoomMax Occupancy: 4 guests (up to 3 children, 1 infant)
Room, 2 Bedrooms, Connecting RoomsMax Occupancy: 4 guests (up to 3 children, 1 infant)
Hotel with a restaurant, in Noisiel (Disneyland Paris)
Collect 200 points
Simply enter your Nectar card number when prompted. Your points will be credited 30 days after you return from your trip.*Offers may apply
This hotel is located in Noisiel (Disneyland Paris), close to Centrex, Centre Commercial les Arcades, and Bay 2. Area attractions also include Bussy-Guermantes Golf Course and Ormesson Golf Club.
Hotel Features
In addition to a restaurant, Hipotel Marne la Vallée features wireless Internet access (surcharge). Other amenities include free self parking and a 24-hour front desk.
Room Amenities
Televisions come with satellite channels. Guestrooms also feature climate control, coffee/tea makers, and desks.Information missing or incorrect? Tell us!
Hotel Amenities
Hotel Amenities
The hotel offers a restaurant. High-speed wireless Internet access is available for a surcharge. This Noisiel hotel also offers tour/ticket assistance, multilingual staff, and an elevator (lift). Complimentary self parking is available on site.
- 24-hour front desk
- Total number of rooms - 59
- Breakfast available (surcharge)
- Elevator/lift
- Tours/ticket assistance
- WiFi (surcharge)
- Luggage storage
- Multilingual staff
- Free self parking
- Restaurant
Available in some public areas: Wireless internet access (3 EUR per 24 hours surcharge)
Free self parking
Room Amenities
- Soundproofed rooms
- Phone
- Coffee/tea maker
- Hair dryer
- Iron/ironing board (on request)
- Desk
- Rollaway/extra beds available
- Satellite TV service
- Free newspaper
- Climate control
Where to Eat
Hipotel Marne la Vallée has a restaurant serving breakfast only.
Hotel Policies
Check-in time starts at Noon
Payment types
Pets allowed, Only dogs are allowed
You need to know
Extra-person charges may apply and vary depending on hotel policy.
Government-issued photo identification and a credit card or cash deposit are required at check-in for incidental charges.
Special requests are subject to availability upon check-in and may incur additional charges. Special requests cannot be guaranteed.
- A tax is imposed by the city: EUR 1 per person, per night
- Breakfast fee: EUR 6 per person (approximately)
- Fee for wireless Internet in public areas: EUR 3 (for 24 hours, rates may vary)
- Pet fee: EUR 5 per pet, per day
National Rating
This hotel has received its official star rating from the French Tourism Development Agency, ATOUT France.


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Garage door reverses after closing
Hi all,
I recently replaced my drive gear which was worn out. I now have a problem where the garage door reverses immediately after closing. The led on the garage door opener does not blink. I have tried:
1. Decreasing the down travel (couple of 360 degree turns clockwise but it didnt help)
2. Decreasing the down force (about 20 degree turn anticlockwise. The force adjustment is pointed to about 4 o'clock.) I didnt try increasing it lest I wear out my drive gear.
I also tried to grasp the door while it was travelling downward but it continues to move down. It doesnt stop. There is no problem when it is travelling up.
Could this be because of a balancing issue or just an adjustments problem.
Thanks in advance for any tips.
Take the cover off the opener and watch the limit switch assembly. I think the down limit is still not adjusted correctly. The correct adjustment for the down force is when the door consistently closes properly. Never increase it unless absolutely necessary. When the door hits the floor before the down limit is contacted the safety circuit in the logic board reverses the door to the open position.

subset: commoncrawl


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This Ford's. I think they're in Florida: Ford's Custom Gun Refinishing - Ford's Desert Eagle Sights
I was lazy and didn't clean my guns from Saturday's range trip until today.
While I was at it, I took the bluing off the Sistema's slide. I mixed up some J-B Weld and filled the import mark. I tried to keep it pretty thin so as to not have to do too much file work. So right now, it's curing and I'll let it set until next weekend.
The plan is to go to my buddy's house and Ceramcoat the pistol there. He's a bachelor and we can stink up his house when the parts bake. My wife wouldn't be pleased with me if I did it at our place.
BTW, the Ladysmith shot like a champ. Not a single hiccup.
Sounds good CA, I hope there wil be plenty of pics of that beauty!!
People get the government they deserve.
I hope it comes out well. The best laid plans and all that...
Post some pictures when you are done
Cummings Custom Refinishing Quality Affordable Firearms Refinishing 423-639-8924
3351 Asheville Hwy Greeneville Tn 37743www.ccrrefinishing.com


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It is a simple application to convert photos into sketches with in few seconds, Share the sketched pics on facebook, twitter, email etc and can select pic from everywhere in your device by share option.
Point & shoot from camera or select from your photo library, and see the sketch right through your device after you pick a picture.
How to use:
1. Pick a picture from your device or just capture by your device camera.
2. Select sketch type or art type.
3. Select options for Go to home, Back, Save.
This application needs internet connection.
Some mobile handsets don't support camera feature inconvenience regretted.
What's New
Sketch Guru
Sketch Guru is a professional app to make you an artist by creating pencil sketch of your photos.
Pick a picture from your gallery or capture one from your camera to generate the sketch.
We support both black-white and color sketch with 13 kinds of wonderful effects including: Gouache, PencilSketch, ColorPencil, WaterColor, HalfTone, SimpleSketch, ComicB&W, BlackBoard, BlackBoardColor, Print, B&W, PencilSketch2 and No sketch
You can also share them on Instagram, Facebook, Twitter, Flickr, E-mail, etc.
SketchGuru is the best sketch app you can find on the market.
Come on and create wonderful and paintings.
* Resize photo: User can adjust the size of the picture by pressing buttons in 6 different ways
* 13 kinds of black-white and color sketch effects supported
Keywords: sketch free, sketch me, pencil sketch, paper camera, cartoon camera
Pencil Sketch
An easy-to-use app to make you an artist by creating pencil sketch of your photos. You can pick a picture from your gallery or capture one from your camera to generate the sketch. Both black-white and color sketch results can be easily created by JUST one button click. There are two styles included in the app: "Sketch" and "Doodle". "Sketch" style creates more accurate results with better edges and curves, which is very good for human portrait photos. "Doodle" style is suitable for objects and nature views, since it is more casual with lower accuracy on edges and curves.
Photo Editor is also built-in within this app, which includes many useful and quick manipulations of your photos, such as drawing, saturation adjustment, filter effects, etc.
Saving images can be done quickly by a single touch of a button. Sharing pics are also supported. Photos can be shared from Facebook, Twitter, E-mail, Message, etc.
Sketch Me
Point & shoot from Android camera, and see the Photoshop effects right through your device camera after you click a picture.
How to use:
1. Pick a picture or image you already have or you just capture;
2. One button to realize the sketch effects;
3. Click on the Share button, share your pictures to your friends;
★ You can choose sketch,crayon,oil paint
★ Sketch and color sketch for selection
★ Use rotation button to adjust the pictures
★ Save to the SD card, you can review at any time
★ Share your pictures to your friends
Pencil Sketch
♥♥♥♥ The best mesmerizing and most easy Pencil Sketch. ♥♥♥♥
♥♥ I convert my picture into cute sketch ♥♥. Simmi
♥♥ Great vintage cartoon sketch, Thanks ♥♥. Danny
Pencil Sketch the best app to create most amazing carton camera effects and pencil sketch of your pictures. Our photo sketch app provides you the facility to convert images into paper camera style.
The free sketch app is enriched with the best high quality photo sketch filters for creating the most adorable sketches of your images.
This sketch me app is also clubbed with the most precise collection of photo sketch frames which can be easily applied to your pencil Sketches.
Our pencil Sketch has the best effects like:
★ The Sketchy Collage Effect
★ The Watercolor Effect
★ The Blackboard Effect
★ The Pencil Camera Effect
★ The Cartoon Effect
★ The Crayon Effect
★ The Sketch Effect
★ The Canvas Effect
★ The Reverse Effect
★ The Gouache Effect
and many more
Our sketch free app gives you the facility to change your simple looking images into high quality paper sketch or high resolution cartoon sketch images easily in few taps.
Our face sketch app provides you the facility of cool text writer to write adorable text on your pencil Sketch, easily save them and share them on your social network.
Pencil sketch Features-
★ Take image from camera or select from gallery.
★ Easily edit pic (Crop, Re-size, Zoom etc.)
★ Easily write cute text on Pencil Sketch.
★ Add astonishing pencil sketch Filters to images.
★ Use the most unique and cute frames for your pencil sketches.
★ Easily change the font size and font color for text in photo sketch.
★ Single tap sharing of sketch on social media.
★ Can be easily shared at all social network.
Photo Sketch
1. Click a photo from camera,or select an image from Phone Gallery;
2. 32 popular filters and effects;
3. Photos save at photoeffects folder.
4. Supports all Android devices above Android version 2.1
Share with your friends through with Instagrm,Twitter,Facebook,Email,WhatsApp Secret or other social networks.
Keywords: pencil, sketch, effects, photography.
XnSketch - Sketch & Cartoon
Different effects easy to use with full control. Save your creations and share them with your friends through Facebook, Twitter, and Email.
----- What people are saying -----
+ Fantastic! Absolutely love what this program does. The effects are really beautiful.
+ This app is very well done
+ Make it more beautiful I think this is absolutely awesome. Thank you!
★ Different effects (black strokes, white strokes, pastel, pencil sketch, color sketch, cartoon, stamp, halftone, hatching, ...)
★ Edge strength, and opacity adjustment
★ Contrast, brightness, saturation adjustment
★ Save or share the result with your friends via Twitter, Facebook, Email, ...
You like XnSketch!? Please give us 5 stars! Your feedback is very important to our work.
Help us to improve XnSketch! by sending your bugs or requests on firstname.lastname@example.com
Facebook: http://www.facebook.com/xnview
Twitter: http://www.twitter.com/xnview
G+: http://plus.google.com/+xnview/
Sketch Me Now
Sketch Me Now is easy to use:
1. Select a Photo from Gallery, Camera or Facebook Photo.
2. Watch the beautiful artistic drawing being drawn on white board.
3. Save and Share the Artistic Picture created with anyone.
Create best pencil drawing like Art with Sketch Me Now in entertaining way.
Sketch Artist
How it works:
+ Click a photo from camera,or select an image from Phone Gallery, Facebook
+ Select the area you want to apply the effect on. ie. Crop and Resize
+ Choose from 20+ photo filters and apply it
+ Apply a beautiful frame to the picture
+ Add text to write on picture
+ Preview the great piece of drawing art you have made
We're waiting for your reviews and suggestions, keep them coming to us : -- email@example.com
Portrait Sketch
You can pick a picture from your gallery or capture one from your camera to generate the sketch. Both black-white and color sketch results can be easily created. Sharing pics are also supported in the app. They can be shared from Facebook, Twitter, E-mail, Message, etc.
A built-in photo editor is included in this app with multiple photo effects. Photo frames were also added recently.
Pencil Camera Face Sketch App
"Woah! Amazing face sketch app, effortlessly Sketch the pic" - Jonna
"I just like the effects its has, amazing Halftone, watercolor and Cartoon Sketch Effects" - Amanda
"love it, this awesome app cartoonized my pics" - Jessica
Sketching is always been fun to look at, but to sketch by urself it was too hard. So Pencil Camera Face Sketch App will do all the sketching stuff and make you sketch artist.
You don't need to know anything about photo editing skills, all you need is this app and your photo and be a sketch guru or lifehacker.
You Don't even need to take black pencil and start sketching like an artist because it automatically done by our algorithms for you.
You can do all the sketchy stuffs to you photos Using the Features in the app and see the effects live; it seems so amazing. you can whiten, sharpen, stroke cartoonize using Pencil Camera Face Sketch App.
Create awesome sketches from your photos! You always wanted to see how your sketch would look. Load your phone with awesome collages. sketch them using photo sketch, you can also create amazing cartoon portrait.
use amazing pencil camera moment effect, or sketch your cartoon avatar, or create awesome color photo sketches.
+ Click a photo from camera,or select an image from Phone Gallery
+ Select the area you want to apply the effect on. ie. Crop and Resize (Zoom ,pan)
+ Choose the Pencil Sketch effect or filter you want to apply
+ Apply a beautiful frame to the picture
+ Add text to write on picture
+ Preview the great piece of drawing art you have made
+ save it on SD card
+ share with your world using the inbuilt features to share on facebook, whatsapp, instagram, flicker, Tumbler, 500px etc.
Face Sketch - Cartoon Cam free brings to you an awesome collection of cartoon and pencil sketch effects, the effects you love to have on your pics. You can browse gallery of clicked photos and share on all your favorite networks, just in one-tap. Use this awesome sketch maker with amazing effects and filters.
Photo Sketch has a lot of great 20+ photo effects like:
- Sketchy Collage Effect
- Watercolor Effect
- Blackboard Effect
- Pencil Camera Effect
- Cartoon Effect
- Crayon Effect
- Sketch Effect
- Canvas Effect
- Reverse Effect
- Gouache Effect
Face Sketch - Pencil Cam free also bring you some of the pro frames that are in the market with overall 25+ amazing frames and makes your life simple and amazing, apply these beautiful frames and make your photos and sketches look epic. Use cool magic frames and show your inner artist
You can also write caption on the images and drag the text on the pictures using the gesture functionality provided in the app, with the option to change the color font style and font size. make instaCaption and put them on your Sketches.
Just download Pencil Camera Face Sketch App and see the magic.
Sketch Master-Pencil Sketch
# Take photo from gallery or camera.
# Crop or re size photo as per your need.
# Rotate photo and adjust it as per requirement.
# Give effect to it, there are many effect, choose out of them.
# There are many overlay, pick any to give overlay.
# Sketch give special effect to your photo, select anyone to apply on photo.
# Save your photo in mobile.
# Share photo to social networking site.
Sketch Camera
just see a different world around you
Many different artistic effects of sketch/cartoon/pencil drawings/oil/watercolor/manga style/noir and many more painted directly in your camera, in real time. You can also apply all those effects to the existing photos of your gallery.
- Apply effects to the photos in your gallery
- Apply real time effects and take photos and videos with your camera
- Option to adjust video quality depending your device capabilities
- Use back and front cameras of your phone
- Pinch to zoom
- You can choose from many effects cartoon, sketch, oil painting, pencil, watercolor, charcoal and many more
- Save images or take a photo quickly by a single touch of a button
- Supports auto focus (tap anywhere on the screen)
- Share photos by email or to social networks like Facebook, Instagram etc
Insta Photo Sketch
- Take a photo from camera, or select from phone library.
- Choose from various sketch photo filters
- Share your creation on social media sites or save them to library.
Create awesome sketches from your photos! It's artistic photo sketch app that lets you convert your simple photos into beautiful sketch photo. So download Insta Photo Sketch now like and become a photo sketch artist.
We are constantly working on making the content and functionality of our apps better. We are always excited to hear from you! If you have any feedback, questions, or concerns, please share with us at: http://apps-ticket.com
Color Pencil Sketch effect
This easy to use app make you an artist by creating a pencil sketch of your photos. Just import pic from gallary or capture from camera to create sketch of your photo.
Both black-white and color sketch results can be easily created by JUST one button click. There are two styles included in the app: "Sketch" and "Doodle".
'Sketch' style creates more accurate results with better edges and curves,which is very good for human portrait photos.
'Doodle' style is suitable for objects and nature views, since it is more casual with lower accuracy on edges and curves.
A magnificent photo editor tool use also built-in within app,which encludes magnificent drawing feature with image effects, Picture editing , Stickers, photo management , photo sharing, Portrait processing is free for you.
Color Pencil Sketch the best app to create most amazing pencil sketch like cartoon sketch of your pictures.
This color photo sketch app provides you the facility to convert images into pencil sketch which is like a paper camera style.
The free sketch app is enriched with the best high quality photo sketch filters for creating the most adorable sketches of your images.
Transform your photo or any kind of picture in an astonishingly realistic pencil sketch or even other type of detailed art, like the ones made by the best professional artists.
Sketch your imagination in an image effect.Color pencil sketch lets you create an awesome pencil drawing from any photograph with a tap & touch!
its comes very close to the hand-drawn works of a human artist.Our android sketching tool works, simply ! Without any complicated tools Color pencil sketch will carry out for you a beautiful pencil drawing effect, and can thus give a unique atmosphere to your photographs.
My Sketch
✔ Top 10 Photography in more than 15 Countries
✔ Over 5 Million Users on Apple AppStore
✔ Over 7 Million Users who has use our Sketch Application on Facebook
✔ Turn your photos to Beautiful Realistic Sketch
✔ Create unlimited sketches
✔ High Resolution
✔ Photos can be taken directly from Camera or Photo Album
✔ Choose 20 different type of Sketches
✔ Adjustment of Brightness and Contrast to achieve the best Sketch Results
✔ Sharing via Facebook,Twitter, Tumblr,Flickr and E-mail
★★Why are we different from the other Sketch Application? ★★
✔ We use complex algorithm to achieve REALISTIC and NEAR PERFECTION Sketch
✔ Our Sketch can be saved into High Resolution and suitable for printing
✔ Our Sketch retain the original quality of the Photo without destroying or distorting it.
Best Regards,
My Sketch - The Best Sketch Creator on Android and iOS Appstore
Sketch Me Effects
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If taught young, self-control skills can have strong protective effects, even helping those whose vulnerabilities might make them more likely to fall behind economically. That's according to Walter Mischel, author of "The Marshmallow Test," in part four of his conversation with Paul Solman. Continue reading
This November, Alaska, Arkansas, Illinois, Nebraska and South Dakota will vote on proposals to raise their states' minimum wages. In Republican-controlled Arkansas, where the hourly wage is lower than the federal minimum, polls show overwhelming support for the measure. Jacob Kauffman of KUAR Public Radio in Little Rock reports. Continue reading
Each of us has our own temptations, says Walter Mischel, author of "The Marshmallow Test." For Mischel, it was smoking. For Clinton, it was junk food. Having the willpower to resist, Mischel explains, requires making the long-term consequences of each of those things more emotionally salient. Continue reading
The first step to overcoming temptations, like eating the marshmallow, is figuring out what makes us "hot." All of our behavior is localized, says "The Marshmallow Test" author Walter Mischel, and our vulnerabilities are no exception. Continue reading
From the father of the Marshmallow Test, Columbia University psychologist Walter Mischel, comes the new book, "The Marshmallow Test: Mastering Self Control." Continue reading
WASHINGTON — The federal government's budget deficit has fallen to $486 billion, the smallest pool of red ink of President Barack Obama's six-year span in office, a new report said Wednesday. Continue reading
As industrial robots continue to acquire cognitive skills, machines will replace one in three human workers by 2025, Gartner analysts predicted Monday. Continue reading
Don't use recruiters who suffer from buzz-word syndrome. They probably don't represent clients you'd want to work for, says headhunter Nick Corcodilos. Continue reading
Larry Kotlikoff explains that remarried retirees cannot collect spousal benefits from an ex-wife or ex-husband, and steers a couple away from a Social Security strategy that wouldn't have worked for them. Continue reading
You've heard about Uber taking business away from traditional taxicab drivers, and their ire toward the competition. But what is it like to drive an Uber, specifically your own car as an UberX? The drivers Making Sen$e spoke to gave Uber, as an employer, a mixed review. Yet none of them wanted to be driving a taxi instead. Continue reading


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In response to:
I think most home schooled do better
Dead Americans are a joke? Liberalism must be a mental disorder.
In response to:
How many times do the Police (Darren Wilson) or private citizens (George ZImmerman) stop bad guys with guns?
Your spam is non sense: are you trying to prove that liberalism is a mental disorder?
Taft you need to take a literacy course: this article is about Ferguson and the behavior of the 'protestors'. The Taxed Enough Already movement is not involved. Or maybe you need mental help.
Ferguson is not about the Taxed Enough Already movement. Taft have you considered taking an adult literacy course?
Is Joshua Williams, a Taxed Enough Already member? If not why are you mentioning him?
In response to:
How about announcing a 3 to 6 month halt of police activity in the areas that are complaining about the Police? Publically identify the areas and let everyone know that you enter at your own risk? The neighbors and businesses who support the Police will still have Law Enforcement Officers working.
In response to:
Taft: wrong cut and paste.


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Same day shipping...FREE (with min $15 order)!
And they actually ship the day they said they did!!
Package this with some great pricing...Read More ->
I live in Alaska and did not want my order setting out in the cold. I asked for a Signature Required special request. MJM responded within minutes to...Read More ->


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High-profile former Griffith candidate Bill Glasson has confirmed his candidacy for the Senate seat vacated by retiring Senator Brett Mason.
Scott Morrison boycott at Sydney Boys High School: alumni say he is 'an embarrassment'
Alexandra Smith Old boys from one of Sydney's most prestigious public schools say they are outraged and disgusted that the federal cabinet minister Scott Morrison will be a special guest at a fundraising event, warning it would be "an embarrassment" to the school to celebrate a man who has "so flagrantly disregarded human rights".
Adopting a child in or out of Australia is far from simple
Judith Ireland Australians have wildly different experiences on their journeys to adopting children.
Ian Macfarlane confident he can secure crossbench deal on renewable energy target
Lisa Cox Industry Minister Ian Macfarlane believes he does not need Labor to pass major reductions to Australia's renewable energy target and can secure a deal with the crossbench.
Bureau of Statistics merger off but fate of census still undecided
Peter Martin The Abbott government has rejected a plan to merge the Bureau of Statistics with the Australian Institute of Health and Welfare, part of a suite of measures put forward by the bureau to help it find savings to upgrade its aged computer systems.
Federal government commits to global accord on climate
Peter Hartcher and Lisa Cox The Abbott government has committed Australia to joining the next big global climate pact.
Labor probed over AWU numbers
Royce Millar and Ben Schneiders Tony Abbott's trade union royal commission has demanded the ALP hand over sensitive details about Bill Shorten's union power base as the commission turns its sights on the rorting of power within the party.
Triggs defends $350,000 compensation recommendation for refugee who killed wife
Dan Harrison Human Rights Commission president Gillian Triggs has defended her recommendation that a refugee who killed his defacto wife should receive $350,000 in compensation for his detention.
How property investing politicians have skin in the game on the negative gearing debate
Fergus Hunter and Gareth Hutchens Australia's federal politicians have been outed as the country's most enthusiastic property investors, casting doubt on their willingness to rein in negative gearing.
Election tally board finds a home at Old Parliament House
Ross Peake The iconic tally board from the former national tally room, previously used for federal elections, will become part of history at Old Parliament House. However, the Museum of Australian Democracy will not have space to display the entire board which is 37 metres wide and seven metres high.


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AYBC basketball program informational meeting and registration tonight
The Alexandria Youth Basketball Club will hold an informational meeting and registration for its developmental basketball program, which begins in November and runs through early March. The meeting will be held today, Monday, October 4 at 7 p.m. at the Broadway Ballroom.
The program is open to all boys and girls in grades 4-8 and will be directed by Alexandria head basketball coaches Forrest Witt and Wendy Kohler, along with the coaches of the varsity basketball staffs.
Are you a newspaper subscriber but you don't have a Digital Access account yet? https://secure.forumcomm.com/?publisher_ID=40&event=subscriber/lookup.
You will need your subscription account number and phone number. Not sure if you have an account? Email us at email@example.com and we can help you.


text:
Previous Episode | Next Episode
Casting CallCasting Call (1987) Season 1 Episode 106- Beverly Hills Teens Cartoon Episode Guide by Dave Koch
This page has been viewed 14 times this month, and 506 times total.
- Beverly Hills Teens Cartoon Episode GuideEpisode GuideTelevisionSeriesCartoon
- Traditional Animation
- DiC Entertainment
- Distributed by: Access Syndication
- Cartoon Characters: Tara, Jett, Shanelle Spencer, Bianca Dupree, Blaze Summers, Larke, Troy, Tiara, Empress, Chester, Jillian, Pierce Thorndyke, Switchboard, Radley, Gig, Wilshire, Nikki Darling, Buck.
- Voice Actors: Michelle St. John, Tracy Moore, Karen Bernstein, Corrine Koslo, Stephen McMulkin, Michael Beattie, Mary Long, Mark Saunders, Jonathan Potts; Full Voice Cast ...
- Produced By Robby London, Andy Heyward.
- Written By Mike O'Mahony.
- First Aired on September 28, 1987.
- Originally Released in Syndication.
- Running Time: 30 minutes.
- Season: 1
- Color
Cartoon Summary:
Every girl in Beverly Hills wants to audition when Buck Huckster plans a production of Romeo and Juliet for the high school "Dramatic Society."
Cartoon Production Information:
Back in the days before cartoons decided to develop a social conscience, Beverly Hills Teens taught the kids at home that classic 80's mantra, "Greed is good." Adding a bit more sass to the classic... (more)
Cartoon Video:
Sorry, we do not have a video of Casting Call. If you have one, or know of one on Youtube, Vimeo or any other site, Let Us Know
Submit Additional Information:
Do you have anything to add to this page? Have we made any mistakes... or do you have any additional information about Casting Call? If so, we would love to hear from you. Please send us a quick note with your additions or corrections to this page, and we will make the corrections as soon as possible!
Cartoon Comments:
Below are comments about this cartoon submitted by people who have seen this show. Take a look and see what others have said about Casting Call. We want to know what you think, too!! Feel free to share your own opinion- we do want to hear from you! You can add your own comments here.


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A few interesting items in classical music news this week:
"Berkeley Rep scrutinized InstantEncore and the competition. We opted for IE and have no regrets. Designing our mobile site and app was affordable, collaborative, and on-time. We launched both, and we love them. We can't wait to see what they do for the Theatre."


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Sweet Jesus
Submitted by Antelmann22 on Mon, 05/06/2013 - 00:23. Permalink
Just for the future. What exactly did I say so wrong? I apologize if I said something bad. Just because I couldn't afford a subscription doesn't mean I haven't been following the site or RP. Jeez and right when I thought you were someone cool in my county.......You seriously bummed me out
- Login to post comments


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Quiz: Remember the definition of mal de mer?
To engage in youthful indiscretions, usually sexual liaisons: "Paul asked his father if he had sowed his wild oats before getting married."
any of several tufted annual grasses of the genus Avena (family Poaceae), native to Eurasia. Wild oats are sometimes cut for hay, and young plants provide forage for grazing animals


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Tag » Flavorwire
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On Newsstands Now: Apr/May 2015
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VIEWS: 448 PAGES: 9 CATEGORY: Research POSTED ON: 10/31/2010
Search-based optimization techniques (e.g., hill climbing, simulated annealing, and genetic algorithms) have been applied to a wide variety of software engineering activities including cost estimation, next release problem, and test generation. Several search based test generation techniques have been developed. These techniques had focused on finding suites of test data to satisfy a number of control-flow or data-flow testing criteria. Genetic algorithms have been the most widely employed search-based optimization technique in software testing issues. Recently, there are many novel search-based optimization techniques have been developed such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Immune System (AIS), and Bees Colony Optimization. ACO and AIS have been employed only in the area of control-flow testing of the programs. This paper aims at employing the ACO algorithms in the issue of software data-flow testing. The paper presents an ant colony optimization based approach for generating set of optimal paths to cover all definition-use associations (du-pairs) in the program under test. Then, this approach uses the ant colony optimization to generate suite of test-data for satisfying the generated set of paths. In addition, the paper introduces a case study to illustrate our approach.
Universal Journal of Computer Science and Engineering Technology 1 (1), 64-72, Oct. 2010. © 2010 UniCSE, ISSN: 2219-2158 A New Software Data-Flow Testing Approach via Ant Colony Algorithms Ahmed S. Ghiduk Department of Computer Science College of Computers and Information Systems Taif University, Taif, Saudi Arabia email@example.com Abstract—Search-based optimization techniques (e.g., hill point inputs because the current constraint solvers cannot solve climbing, simulated annealing, and genetic algorithms) have been floating point constraints. applied to a wide variety of software engineering activities including cost estimation, next release problem, and test Dynamic test-data generation techniques collect generation. Several search based test generation techniques have information during the execution of the program to determine been developed. These techniques had focused on finding suites of which test cases come closest to satisfying the requirement. test data to satisfy a number of control-flow or data-flow testing Then, test inputs are incrementally modified until one of them criteria. Genetic algorithms have been the most widely employed satisfies the requirement [5, 6]. Dynamic techniques can stall search-based optimization technique in software testing issues. when they encounter local minima because they depend on Recently, there are many novel search-based optimization local search techniques such as gradient descent. techniques have been developed such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Immune Search-based optimization techniques (e.g., hill climbing, System (AIS), and Bees Colony Optimization. ACO and AIS have simulated annealing, and genetic algorithms) have been applied been employed only in the area of control-flow testing of the to a wide variety of software engineering activities including programs. This paper aims at employing the ACO algorithms in cost estimation, next release problem, and test-data generation the issue of software data-flow testing. The paper presents an ant [7]. colony optimization based approach for generating set of optimal paths to cover all definition-use associations (du-pairs) in the Several search based test-data generation techniques have program under test. Then, this approach uses the ant colony been developed [8, 9, 10, 11, 12, 13]. Some of these techniques optimization to generate suite of test-data for satisfying the had focused on finding test data to satisfy a wide range of generated set of paths. In addition, the paper introduces a case control-flow testing criteria (e.g., [8, 10, 11]) and the other study to illustrate our approach. techniques had concentrated on generating test-data for covering a number of data-flow testing criteria [12, 13, 9]. Keywords- data-flow testing; path-cover generation, test-data Genetic algorithms have been the most widely employed generation; ant colony optimization algorithms search-based optimization technique in software testing area [7]. I. INTRODUCTION Recently, there are some novel search-based optimizations There are many critical activities associated with software techniques have been developed such as Ant Colony testing such as 1) finding path-cover to cover a certain testing Optimization (ACO) [14, 15], Particle Swarm Optimization criterion 2) test-data generation to satisfy the path cover, 3) test (PSO) [16], Bees Colony Optimization [17], and Artificial execution by using the test data and the software under test and Immune System (AIS) [18]. There are few efforts for applying 4) evaluation of test results. A number of test-data generation some of these novel search-based optimization techniques in techniques have been developed. the area of software testing [18, 19, 20, 21, 22, 23, 24, 25, 26]. Random test-data generation techniques select inputs at Ant Colony Optimization (ACO) has been applied in the random until useful inputs are found [1, 2]. This technique may area of software testing in 2003 [19, 20]. Boerner and Gutjahr fail to find test data to satisfy the requirements because [19] described an approach involving ACO and a Markov information about the test requirements is not incorporated into Software Usage model for deriving a set of test paths for a the generation process. software system, and McMinn and Holcombe [20] reported on the application of ACO as a supplementary optimization stage Symbolic test-data generation techniques assign symbolic for finding sequences of transitional statements in generating values to variables to create algebraic expressions for the test data for evolutionary testing. H. Li and C. P. Lam [21, 22] constraints in the program, and use a constraints solver to find a proposed an Ant Colony Optimization approach to test data solution for these expressions that satisfies a test requirement generation for the state-based software testing. Bouchachia [3, 4]. Symbolic execution cannot determine which symbolic [18] incorporated immune operators in genetic algorithm to value of the potential values will be used for array as B[c] or generate software test data for condition coverage. Ayari et al. pointer. Furthermore, symbolic execution cannot find floating 64 Corresponding Author: Ahmed S. Ghiduk, Department of Computer Science, Taif University, Saudi Arabia UniCSE 1 (1), 64 -72, 2010 [23] proposed an approach based on ant colony to reduce the associated with graph components (either nodes or edges) cost of test data generation in the context of mutation testing. whose values are modified at runtime by the ants. Figure 1 Srivastava and Rai [24] proposed an ant colony optimization shows a generic ant colony algorithm. based approach to test sequence generation for control-flow based software testing. K. Li et al. [25] presents a model of Step 1: Initialization generating test data based on an improved ant colony – Initialize the pheromone trail optimization and path coverage criteria. P. R. Srivastava et al. Step 2: Iteration [26] presents a simple and novel algorithm with the help of an – For each Ant Repeat – Solution construction using the current pheromone trail ant colony optimization for the optimal path identification by – Evaluate the solution constructed using the basic property and behavior of the ants. – Update the pheromone trail – Until stopping criteria However, data-flow testing is important because it Figure 1. A generic ant colony algorithm augments control-flow testing criteria and concentrates on how a variable is defined and used in the program, which could lead The procedure to solve any optimization problem using to more efficient and targeted test suites. The results of using ACO is: ant colony optimization algorithms in software testing which 1) Represent the problem in the form of sets of obtained so far are preliminary and none of the reported results components and transitions or by means of a weighted graph directly addresses the problem of test-data generation or path- that is traveled by the ants to build solutions. cover finding for data-flow based software testing. 2) Appropriately define the meaning of the pheromone This paper aims at employing the Ant Colony Optimization trail, i.e., the type of decision they bias. This is a crucial step algorithms in the issue of software data-flow testing. To our in the implementation of an ACO algorithm. A good definition knowledge, this paper is the first work using ACO in the issue of the pheromone trails is not a trivial task and it typically of data-flow testing. The paper presents an ant colony requires insight into the problem being solved. optimization based technique for generating set of optimal 3) Appropriately define the heuristic preference to each paths to cover all definition-use associations (def-use or du- decision that an ant has to take while constructing a solution, pairs) in the program under test. Then, this technique uses also i.e., define the heuristic information associated to each the ant colony optimization algorithms to generate suite of test- data for satisfying the generated set of paths. In addition, the component or transition. Notice that heuristic information is paper introduces a case study to illustrate our approach. crucial for good performance if local search algorithms are not available or cannot be applied. The rest of the paper is organized as follows. Section 2 4) If possible, implement an efficient local search gives some basic concepts and definitions. Section 3 introduces algorithm for the problem under consideration, because the two ant colony algorithms for using with data-flow testing. One algorithm generates set of paths for covering all def-use pairs in results of many ACO applications to NP-hard combinatorial the software under test (SUT) and the other algorithm finds set optimization problems show that the best performance is of test data to satisfy this set of paths. Section 4 presents a achieved when coupling ACO with local optimizers. technique for implementing the two algorithms in data-flow 5) Choose a specific ACO algorithm and apply it to the testing. Section 5 presents a case study to illustrate our problem being solved, taking the previous aspects into approach. Section 6 introduces conclusion and future work. consideration. 6) Tune the parameters of the ACO algorithm. A good II. BACKGROUND starting point for parameter tuning is to use parameter settings This section gives set of basic concepts and definitions that were found to be good when applying the ACO algorithm which will help in understanding this work. to similar problems or to a variety of other problems. It should be clear that the above steps can only give a very A. Ant Colony Optimization rough guide to the implementation of ACO algorithms. In Ant Colony Optimization (ACO) is a population-based, addition, the implementation is often an iterative process, general search technique for the solution of difficult where with some further insight into the problem and the combinatorial problems, which is inspired by the pheromone behavior of the algorithm; some initially taken choices need to trail laying behavior of real ant colonies. The first ACO be revised. Finally, we want to insist on the fact that probably technique is known as Ant System [14] and it was applied to the most important of these steps are the first four, because a the traveling salesman problem. Since then, many variants of poor choice at this stage typically can not be made up with pure this technique have been produced. Dorigo and Blum in [27] parameter fine-tuning. surveyed the theory of ant colony optimization. In ACO, a set An ACO algorithm iteratively performs a loop containing of software agents called artificial ants search for good the following two basic procedures: solutions to a given optimization problem. To apply ACO, the optimization problem is transformed into the problem of 1) A procedure for specifying how the ants finding the best path on a weighted graph. The artificial ants construct/modify solutions of the problem to be solved; (hereafter ants) incrementally build solutions by moving on the 2) A procedure to update the pheromone trails. graph. The solution construction process is stochastic and is The construction/modification of a solution is performed in biased by a pheromone model, that is, a set of parameters a probabilistic way. The probability of adding a new item to 65 UniCSE 1 (1), 64 -72, 2010 the current partial solution is given by a function that depends criterion if it covers the set of entities associated with that on a problem-dependent heuristic and on the amount of criterion. Depending on the criterion selected, the entities to be pheromone deposited by ants on the trail in the past. The covered may be derived from the program control flow or form updates in the pheromone trail are implemented as a function the program data flow. Frankl and Weyuker in [28, 29] defined that depends on the rate of pheromone evaporation and on the a family of popular control flow and data flow test coverage quality of the produced solution. criteria. Data-flow testing considers the possible interactions B. Data-flow analysis and testing between definitions and uses of variables. Typically, in structural testing strategies a program's structure is analyzed on the program flow-graph, i.e., an The occurrences of a variable in a program can be annotated directed graph which represents graphically the associated with the following events: information needed to select the test cases. A statement storing a value in a memory location of a A control-flow graph (CFG) is a directed graph G=(V,E), variable creates a definition (def) of the variable. with two distinguished nodes— a unique entry n0 and a unique A statement drawing a value from the memory location exit nk. V is a set of nodes, where each node represents a of a variable is a use of the currently active definition statement, and E is a set of directed edges, where a directed of the variable. In particular, when the variable appears edge e = (n,m) is an ordered pair of adjacent nodes, called tail on the right-hand side of an assignment statement it is and head of e, respectively. Figure 2(a) gives an example called a computational use (c-use), when the variable program Program1 and figure 2(b) gives its control-flow graph. appears in the predicate of the conditional statement it #include <iostream.h> is called a predicate use (p-use) [29]. void main() entry { A statement kills the currently active definition of a int a, b, c, n; variable when its value becomes unbound. 1 cin >> a >> b; 2 if(a < 6) 1 A path is def-clear path with respect to a variable if it { contains no new definition of that variable. 3 c = a; } T 2 Data flow analysis determines the defs of every variable in F else { the program and the uses that might be affected by these defs 4 c = b; 3 4 (i.e. the du-pairs). Such data flow relationships can be } represented by the following two sets: 5 n = c; 6 while(n < 8) 5 dcu(i), the set of all variable defs for which there are { def-clear paths to their cuses at node i; and 7 if(b > c) { F 6 T dpu(i, j), the set of all variable defs for which there are 8 c = 2; def-clear paths to their p-uses at edge (i,j) [30]. } 7 T F else 11 Using information concerning the location of variable defs { and uses, together with the ‗basic static reach algorithm' [31], 9 n = n + c + 7; 8 9 the sets dcu(i) and dpu(i, j) can be determined [30]. Tables 1 } exit 10 n = n + 1; and 2 show samples of the du-pairs of Program1. 10 } 11 cout << a << b << n; } TABLE V. LIST OF DCU-PAIRS FOR PROGRAM1. (a) (b) dcu variable def-node use-node killing nodes Figure 2. An example program (a), and its control-flow graph (b) 1 a 1 3 None A path p in a CFG is a finite sequence of nodes connected 2 c 8 9 3, 4 by edges e.g., 1→2→3→5 and 2→4. TABLE VI. LIST OF DPU-PAIRS OF PROGRAM1. The key question addressed in software testing is how to select test cases with the aim of uncovering as many defects as dpu variable def-node use-edge killing nodes 1 a 1 (2,3) None possible. 2 n 5 (6,7) 10 There are many activities normally associated with software testing such as 1) path-cover finding to cover a certain testing III. APPLYING ACO TO DATA-FLOW BASED TESTING criterion 2) test data generation to satisfy the path cover, 3) test In order to apply ACO for generating test data or path cover execution involving the use of test data and the software under or any software testing activity, the following number of issues test (SUT) and 4) evaluation of test results. need to be addressed: Coverage criteria require that a set of entities of the 1) Problem representation: transformation of the testing program control-flow graph to be covered when the tests are problem into a searching model (e.g., control-flow graph); executed. A set of complete paths (path cover) satisfy a 66 UniCSE 1 (1), 64 -72, 2010 2) A heuristic measure for measuring the ―goodness‖ of the ant and is not killing node, then ant will select v2 as the paths through the graph (e.g., how far is it from covering the next position that means the path (v1→v2) is traversed. target); P.2) If current node v1 is direct connected to more than one 3) A mechanism for creating possible solutions efficiently node say v2 and v3 and both of them are not visited yet by and a suitable criterion to stop solution generation; the ant and are not killing node, then ant will select the 4) A suitable method for updating the pheromone; and nearest one to the use node as the next position that means if 5) A transition rule for determining the probability of an v3 is closer than v2 from the use node then path (v1→v3) is ant traversing from one node in the graph to the next. traversed. In the following subsections, we introduce two ant colony P.3) If there are many nodes have the same properties then algorithms for using with data-flow testing. The first algorithm the ant will select any feasible path randomly. generates set of paths for covering all def-use pairs in the SUT P.4) The algorithm will stop if selection is not possible that and the second algorithm finds set of test data to satisfy this set means the current def-use pair is infeasible. of paths. P.5) For loop the node will select two times at maximum. P.6) An ant selects use node as the next node, means ant will A. Path-Cover generation select path from current node to use node. The first aim of the paper is driving a path-cover for P.7) The algorithm will randomly select path from the start covering all def-use pairs in the SUT using an ant colony node to the def node and another path from the use node to optimization algorithm. In this section we will modify and adapt the ant colony optimization algorithm which was the end node to construct a complete path. suggested by Srivastava et al. in [26] to be correct and 3) Information Updating appropriate for data-flow testing. In the proposed algorithm ant has ability to collect the knowledge of all feasible paths from its current position. An 1) Problem Representation approach for feasibility check of the paths from current node is The purpose of the ant colony optimization algorithm is used. This approach is defined in feasibility set of path (Fij). finding for each feasible def-use pair at least one def-clear The ant also has four other facts about path: path in CFG graph of the software under test. Therefore, we will use the control-flow graph as the searching model. In a) Pheromone level on path (τij), addition, ants will start at the def node and travel to the use b) Heuristic information for the paths (ηij), node to find the def-clear path from the def node to the use node. Then, the algorithm will randomly select path from the c) Visited nodes with the help of visited status (Vs), and start node to the def node and another path from the use node d) Probability level L. to the end node to construct a complete path. After selection of a particular path ant will update the For example, the control-flow graph in Figure 2(b) is the pheromone level as well as heuristic value. Pheromone level is searching model for example program in Figure 2(a). In increased according to last pheromone level and heuristic addition for the def-use (c, 8, 9), ants will start their search at information but heuristic information is updated only on the node 8 and travel to the destination node 9. basis of previous heuristic information. 2) Path Selection Suppose that an ant t at node "i" and another node "j" which Path selection depends upon the probability of this path. is directly connected to "i", it means there is a path between The path with high probability has high chances to be selected the nodes "i" and "j" (i.e., i→j). In the graph this path by the ant. The probability value of path depends upon: associated with five values Fij(t), τij(t), ηij(t), Vs(t) and Lij(t) where t shows that values associate with ant t. The description a) Feasibility of path (Fij), which shows that there is of these attribute is given below [12]: direct connection between the nodes and there is no killing nodes on this path; 1) Feasible path set: F = {Fij (t)} represents the direct connection with the current node "i" to the neighboring node b) Pheromone trail value (τij), which helps other ants to "j". Direct connection shows that the nodes which are adjacent make decision in the future (i.,e, guides the ants to the good to the current node "i", i.e. a direct edge exist in between the path), and current node "i" and the chosen node "j". c) Heuristic information (ηij) of the path, which Fij =1 means that path between the node "i" and "j" is indicates the visibility of a path for an ant at the current node. feasible and node "j" is not a killing node. In some cases there are more then one feasible path has the Fij=0 means the path between the node "i" and node "j" asme probability vale then by the following policies the is not feasible or node "j" is a killing node for the algorithm selects one of these feasible paths. current def-use. P.1) An ant will select the next position according to the 2) Pheromone trace set: τ = τij (t) represents the value of visited status parameter (Vs). If current node v1 is pheromone level on the feasible path (i→j) from current node direct connected to the node say v2 and v2 not visited yet by "i" to next node "j". The pheromone level is updated after the 67 UniCSE 1 (1), 64 -72, 2010 particular path traversed. This pheromone helps other ants to entry make decision in future. 3) Heuristic set: η = ηij (t) indicates the visibility of a path D11 D12 D13 D1n for an ant at current node "i" to node "j". 4) Visited status set: Vs shows information about all the nodes which are already traversed by the ant t. For any node D21 D22 D23 D2n "i": Whereas Vs (i) =1 indicates that node "i" is already visited by the ant t. Vs (i) =0 shows that node "i" is not visited yet by the Dk1 Dk2 Dk3 Dkn ant t. exit 5) Probability set: Selection of path depends upon Figure 3. The searching model diagram probabilistic value of path, because it is inspired by the ant behavior. Probability value of the path depends upon the 2) Path Selection feasibility of path Fij(t), pheromone value τij(t) and heuristic After constructing the representation graph, this part will information ηij(t) of path for ant t. There are two more introduce the main process for selecting the test data. At first parameter α and β which used to calculate the probability of a putting a certain number of ants at the start node of the model, path. These parameters α and β control the desirability versus then the ant selects a branch to move until getting to the end visibility. α and β are associated with pheromone and heuristic node. According to the number of each node record in each value of the paths respectively. layer, we can use the data generation functions to get the The proposed ant colony algorithm helps to get not only corresponding data in the corresponding interval. Then we use knowledge of present node but also all feasible paths from these data to drive the tested program to run, calculate the current node to next node and historical knowledge of already executed path and compare it with the def-clear path which traversed paths and nodes by the ant. will influence the release of pheromone. The pheromone can be updated according to the updating rules. B. Test-data generation 3) Information Updating The second aim of this paper is generating a set of test data to cover all def-use pairs of the SUT. In this section we will a) The Rules of Pheromone Update introduce an adaptation for the ant colony optimization In this approach, modified ant density model is used to algorithm which was suggested by K. Li et al. in [25] to be update pheromone. The original ant density model is as suitable to data-flow testing. follows: Q if ant passes ij 1) Problem Representation ij (t , t 1) k The first problem is how to represent the problem in a 0 otherwise model which is traveled by the ants to build solutions. The In the initial density model for any ant k, Q is a constant, problem can represent in ordered and circular graph [23] or in that is, the increment of pheromone is a fixed value. The new hierarchical model [25]. In this paper, we augment the Q defined in this paper is the number of common nodes hierarchical model with a start node and we use it to represent between the executed path and the def-clear path of the current the problem. The hierarchical model is created by using the def-use pair. input domain of program. Suppose that the input set of The formula of updating pheromone is: program Prog is A={x , x , x …….x }. Assume that xi has an 1 2 3 k input domain Di, i {1, 2, 3…k}. Each input domain Di is ij (t n) (1 ) ij (t ) ij divided into sub-domains D , Di2…Din. Finally, a hierarchical i1 b) The Rules of Next node Selection model is built like Figure 3. Because of the lack of pheromone information in the initial The links between layer and layer are complete in this search, ant colony algorithm might easily fall into local model. By searching the model, we could find the combination optimization. The paper proposes such a strategy, that is, at the between set n in layer i and set m in layer j. The data generated early stage of searching, letting the ant choose the path that from the sets n and m will have a higher possibility to satisfy has the smallest pheromone and ignore the impact of the selected path. According to the analysis of these pheromone. In short, we call it the ―choose the poorest‖ combinations of layers, it is not difficult to obtain the strategy. After several iterations, the algorithm abandons this distribution of the data that satisfies the selected path. strategy, turning to determine the selection of path which has the most pheromone. The aim of this strategy is to allow ants to explore more paths at the early stage of searching in order to avoid searching partial paths and prevent the algorithm from falling into local optimization. In this way, the new rules for next node selection (i.e., state transition) are: 68 UniCSE 1 (1), 64 -72, 2010 when m <= tempnum Input Domains next_node(i)=min(τij ) Test data searching model Testing Criterion (C) Inputs Outputs /* next_node(i) returns next node which connects with i*/ Analysis Module /* min(τij) return node j that connects with node i and path ij has Classify and Reformat Software under test (SUT) the least pheromone */ Control Flow Graph m++; Inputs (CFG) Inputs User Path Cover Entities to be covered when tempnum < m < maxnum Generation Module (Ec) next_node(i)=max(τij) Outputs Set of Paths (P) /* max(τij) return node j that connects with node i and path ij has Outputs Inputs Test data searching model the most pheromone */ Test-Data m++; Generation Module /*tempnum denotes the iterations times which uses the "choose the poorest" strategy. maxnum denotes the total iterations times of the Figure 4: The block diagram of the proposed technique algorithm. m denotes the loop counter.*/ B. Path-Cover Generation Module In the next section, we present an ACO approach using the The path-cover generation module uses the following above information to automatically generate path cover and test algorithm to generate set of paths to cover all the def-use data from the control-flow graph for data-flow based software associations in the software under test. The algorithm easily testing. traverses all the nodes and derives a set of paths which is required for all def-use coverage criterion. IV. OUR PROPOSED APPROACH Algorithm for ant t: In this section we describe our proposed approach for data- Step 0: for each def-use pairs do steps from 1 through 3 flow testing of C++ programs. This approach based upon the 0.1 Select DU: select uncovered yet def-use pair to be ant colony optimization algorithms in section III to solve the covered. problem of deriving a path cover for the def-use associations of 0.2 Set start and end node: set the start node to be the def the program under test and generating a set of test data that satisfies this path cover. Figure 4 shows the overall diagram of node and the end node to be the use node. our proposed technique. Step 1: Initialize all parameter 1.1 Set heuristic Value (η): for every branch (i.e., branch is Our proposed technique performs the following tasks: a connection between two nodes) in the CFG initialize 1) Analysis and reformatting of source code. heuristic value η =2. 2) Generating set of program entities to be covered (i.e., 1.2 Set pheromone level (τ): for every branch in the CFG all def-use pairs). initialize pheromone value τ =1. 3) Generating set of paths to cover the all def-use pairs 1.3 Set visited status (Vs): for every node in the CFG Vs=0 using ant colony algorithm in section III (A). (initially no node is visited by the ant). 4) Generating set of test data using ant colony algorithm in 1.4 Set Probability level (L): for each branch in the CFG section III (B) to satisfy the set of paths. initialize probability L=0. The technique performs these tasks in three stages. We 1.5 Set α=1, and β= 1, here α and β are the parameter give a detailed description of these three stages of the which controls the desirability versus visibility i.e. technique in the following subsections. desirability means if an ant wants to traverse any particular path on the basis of pheromone value and A. Analysis Module visibility means the solution which ant has on the basis The analysis and reformatting module has been built to of prior experience regarding the path. These perform the following tasks: parameters are associated with pheromone and heuristic values of the paths respectively. 1) Read the program under test, testing criterion and input 1.6 Set count: count = cc cyclometic complexity describes domains of the variables. the different possible paths in CFG. The technique 2) Classify program statements and reformats some of automatically calculates the maximum number of them to facilitate the construction of the program control-flow possible paths depending upon the value of number of graph. cc value. 3) Construct the control-flow graph of the reformatted 1.7. Set key: key = end _node, it is a variable which store version of the program. the value of end node. 4) Construct the test data searching model in Figure 3 by Step 2: Repetition the following steps while count > 0 using the input domains of the input variables. 2. While (count>0) 5) Produce the set of entities to be covered that satisfies Evaluation at node "i" the def-use associations criterion. 2.1. Initialize: start=i , sum=0, visit=0. 6) Instrument the program under test to trace and calculate visit is a variable which used to discard a redundant the executed path. path and sum used to calculate the value of strength of 7) Pass the searching model and the input domains of the the path, which later used to prioritize the paths. variables for the test data generation module. 69 UniCSE 1 (1), 64 -72, 2010 2.2. Update the track: Update the visited status for the End //end of algorithm current node "i" Variable count represents the cyclomatic complexity of a i.e. if (Vs[i] ==0) then Vs[i] =1 And visit =visit+1 method, as count becomes zero; it shows all the decision /*increase the value of variable visit*/. nodes traversed. Algorithm will stop automatically in two 2.3 Evaluate Feasible Set: Means to determine F(t) for the condition, firstly if there is no feasible def-use pairs and current node "i", this procedure evaluate the entire secondly if the all feasible def-use pairs are covered at least possible path from the current node "i" to the all the once. neighboring nodes with the help of CFG diagram. If there is no feasible path then go to step 3. C. Test Data Generation Module 2.4 Sense the trace: To sense the trace, evaluate the The test-data generation module uses the following probability from the current node "i" to all non-zero algorithm to generate set of test data to satisfy the set of paths connections in the F(t), as discussed earlier ant's in the path cover. The algorithm easily traverses all the nodes behavior is probabilistic. For every non-zero element and derives the required set of data. belongs to feasible set F(t), we calculate probability Initializing Steps: with the help of below formula. 1. Build the searching model as in Figure 3. ( ij ) (ij ) 2. Select one def-clear path from the path cover and Lij k mark it. (( ik ) (ik ) ) 3. Put ants at start node of the searching model. 1 Moving Ants Steps: For every k belongs to feasible set F(t). 4. Ant moves and records the number of node. 2.5. Move to next node: Using the below rule move to next 5. if (ant not get to the end node) goto step 4. node 6. Record the path R1: Select paths (i→j) with maximum probability (Lij). 7. Generate the corresponding data. R2: If two or more paths (e.g., i→j and i→k) have 8. Execute the program under test using the generated equal probability level like (Lij = Pik) then select path data and record the execution path. according to below rule: 9. Compute the similarity between the execution path R2.1. Compare each entry in the feasible set with the and the def-clear path. end_node 10. Update pheromone. If (feasible set entry==end _node) then select end_ 11. if (execution path not cover the def-clear path) goto node as the next node otherwise follow R2.2. step 3. R2.2. Select that path which have next node not 12. record the test data visited yet (i.e., Visited status Vs =0). If two or more 13. if (there is unmarked def-clear path in the path cover) nodes have same visited status i.e. Vs[j] =Vs[k] then goto step 2 follow R2.3. 14. Output the set of test data and the set of covered def- R2.3. if Vs[j] =Vs[k] then select randomly clear paths. 2.6. Update the parameter: 15. End // the algorithm 2.6.1 Update Pheromone: Pheromone is updated for Algorithm will stop automatically if there are no path (i→j) according to the following rule unmarked def-clear paths in the path cover. (τij)= (τij) + (ηij ) α –β 2.6.2 Update Heuristic: ηij = 2*(ηij ) V. CASE STUDY 2.7. Calculate Strength: It shows the values associated We have developed a prototype tool called PCTDACO with each path using the proposed algorithms to automatically derive a path sum = sum + τij cover for all def-use pairs in the program under test and strength [count] = sum. generate a set of test data for this path cover. The proposed start = next_node. prototype is implemented by using C++ based on the above 2.8. if (start! = end_node) then go to step 2.3 else if algorithms. This tool is fully automatic because it takes only (visit==0) then discard the path it is the redundant path as inputs the program under test, input domains of the input otherwise add new path. variables of the program under test. Tool gives output analysis 2.9. Update count: decrement count by one each time. in file format. The tool also produces a file contains the def- count =count-1. use pairs, the path which covers it, and test data which satisfy Step 3: Complete the generated path this path. Tester can see the internal values generated by ant 3.1 Randomly select a path from the beginning of the like heuristic, pheromone values, probability calculation and describe selection of best path according to algorithm. control-flow graph to the def node. 3.2 Randomly select a path from the use node to end PCTDACO tool automatically calculates the total number node of the control-flow graph. of nodes. 3.3 Select another uncovered def-use pair and go to step For generating the path cover, an ant must start from the 0. def node and it can generate a def-clear path. Def-clear path 70 UniCSE 1 (1), 64 -72, 2010 depends upon the feasibility of path from the current node to node "9" as the next node then update parameter along with other nodes and accordingly it will take decision for further calculation of Strength. The current ant traveled the path proceeding and in the end it gives the optimal test path in CFG 8→10→6→7→9 and reached the end node which is the use diagram of software under test. Here optimal means all node of the current def-use (node 9). Therefore, the tool will decision nodes traversed at least once. save the current def-use (i.e., (c,8,9)) and its def-clear path (i.e., 8→10→6→7→9). Then, the tool randomly generates Table 3 shows the different def-clear paths which are any path from the entry node of the CFG to the def-node (node associated the set of def-use pairs of the example program in 8) and another path from the use node (node 9) to the exit Figure 2. node of the CFG. The tool can generate the paths TABLE III. A SET OF DEF-CLEAR PATHS entry→1→2→3→5→6→7 and 10→ 6→11→exit. Then, the Def-use pairs Def-clear path complete path which cover the def-use (c,8,9) is (a,1,3) 1→2→3 entry→1→2→3→5→6→7→8→10→6→7→9→10→6→ (c,8,9) 8→10→6→7→9 11→exit. (a,1,[2,3]) 1→2→3 (n,5,[6,7]) 5→6→7 The tool repeats the above policy with all def-use pairs to Table 4 shows the different complete paths which are complete the path cover. covered the of def-use pairs (c,8,9). For generating the test data, an ant must start from the TABLE IV. A SET OF COMPLETE PATH COVER entry node of the searching model in Figure 3 and it can Def-use pairs Complete paths generate test datum. entry→1→2→3→5→6→7→ 8→10→6→7→9→10→6→11→exit In our case study, we set the range of each input variable (c,8,9) entry→1→2→4→5→6→7→ of the example program Program 1 (variables a and b) is 8→10→6→7→9→10→6→11→exit 1~100 and divide each range into four smaller ranges: 1~25, Table 5 shows a complete path cover which is covered the 26~50, 51~75, 76~100. We select the path of set of def-use pairs of the example program in Figure 2. entry→1→2→3→5→6→7→8→10→6→7→9→10→6→ TABLE V. A COMPLETE PATH COVER 11→exit as the target path. The model we built for this Def-use pairs Complete paths experiment is as follows: entry→1→2→3→5→6→7→ entry (a,1,3) 8→10→6→7→9→10→6→11→exit entry→1→2→4→5→6→7→ (c,8,9) 8→10→6→7→9→10→6→11→exit 1-25 26-50 51-75 76-100 (a,1,[2,3]) entry→1→2→3→5→6→11→exit (n,5,[6,7]) entry→1→2→4→5→6→7→9→10→6→11→exit 1-25 26-50 51-75 76-100 Our approach arranges the set of complete paths for the same def-use pairs in a priority depending upon the strength of the path (i.e., according to the length of each path) such that exit the short path has a higher priority than the long one. For Figure 5. The searching model for example program example, for the def-use (a,1,[2,3]) the complete path The tool starts the by putting n ants at the entry node of the entry→1→2→3→5→6→11→exit has a higher priority than searching model. Suppose ant "t" randomly selects the first the complete path entry→1→2→3→5→6→7→8→10 node (domain 1 to 25) at the first layer. Then, the ant will →6→7→9→10→6→11→exit. select the second node (domain 26-50) in the second layer. The brief description about how the def-clear path Then the ant will get the exit node. Suppose the corresponding 8→10→6→7→9 is generated for the def-use pairs (c,8,9) in data are 6 and 30. Then the tool executes the program under the CFG of the example program Program1 is given in the test using the data and record the executed path. The executed below. path is entry→1→2→3→5→6→7→ 8→10→6→7→8→10→6→7→10→6→11→exit. Then, the The tool selects the def-use pairs (c,8,9) and initializes all tool updates the pheromone and repeats the above strategy parameter according to step 1, as it is clear from the algorithm until getting the required test data which execute a path covers of path cover generation. The tool put an "t" ant at def node the selected path. The tool repeats the same strategy with each (node 8), for def node tool which generate the feasible set path in the path cover. F(def) = {10} and ant move to next node 6 as there is no decision node from def node to node 6,ant keep on moving and update all values as per algorithm. At node 6 feasible set VI. CONCLUSION AND FUTURE WORK i.e. F[6] ={7,11} with equal probability and visited status L(6- To our knowledge, this paper is the first work using ACO in 7) = L(6-11) and V[7] = V[11] = 0, so according to R3 ant the issue of data-flow testing. This paper aims at employing the select a node randomly from nodes 7 and 11. Suppose the Ant Colony Optimization algorithms in the issue of software algorithm selects node 7 as the next node then update data-flow testing. The paper presented an ant colony parameter along with calculation of Strength. optimization based approach for generating set of optimal paths At node 7 feasible set i.e. F[7] ={8,9} with probability to cover all definition-use associations (du-pairs) in the level L(path7-9) > L(path 7-8) so according to R2.1 ant select program under test. This approach uses also the ant colony 71 UniCSE 1 (1), 64 -72, 2010 optimization algorithms to generate suite of test-data for [18] A. Bouchachia, ―An immune genetic algorithm for software test data satisfying the generated set of paths. The ant colony algorithms generation‖ Proc. of 7th International Conference on Hybrid Intelligent Systems (HIS'07), Sept. 2007, pp. 84-89. IEEE Press. are adopted to search the CFG and a model built on the [19] Doerner, K., Gutjahr, W. J., ―Extracting Test Sequences from a Markov program input domain in order to get the path cover and the test Software Usage Model by ACO‖, LNCS, Vol. 2724, pp. 2465-2476, data that satisfies the selected path. Springer Verlag, 2003. Our future work will focus on estimates the efficiency of [20] McMinn, P., Holcombe, M., ―The State Problem for Evolutionary Testing‖, Proc. GECCO 2003, LNCS Vol. 2724, pp. 2488-2500, ant colony optimization algorithms against genetic algorithms Springer Verlag, 2003. in this area. In addition, we will concentrate on solving the [21] H. Li and C. P. Lam, ―Software test data generation using ant colony problem of constructing the searching model for the program optimization‖ World Academy of Science, Engineering and Technology with input variable of boolean and character type. In addition, vol.1, 2005, pp.1-4. how to revise the model to be applied to object-oriented [22] H. Li and C. Peng LAM , ―An Ant Colony Optimization Approach to programs? Test Sequence Generation for State based Software Testing‖, Proceedings of the Fifth International Conference on Quality Software (QSIC'05), pp 255 – 264,2005. REFERENCES [23] K. Ayari, S. Bouktif, and G. Antoniol, ―Automatic mutation test input [1] H. D. Mills, M. D. Dyer, and R. C. Linger, ―Cleanroom software data generation via ant colony,‖ Proc. of International Conference on engineering,‖ IEEE Software, vol. 4, pp. 19-25, 1987. Genetic and Evolutionary Computation Conference (GECCO'07), July [2] J. M. Voas, L. Morell, and K. W. Miller, ―Predicting where faults can 2007, pp 1074-1081. ACM Press. hide from testing,‖ IEEE, vol. 8, pp. 41-48, 1991. [24] P. R. Srivastava, and V. K. Rai ―An ant colony optimization approach to [3] W. E. Howden, ―Symbolic testing and the DISSECT symbolic test sequence generation for control flow based software testing‖ Proc. evaluation system,‖ IEEE Transactions on Software Engineering, vol. 3, of 3rd International Conference on Information Systems, Technology no. 4, 266-278, 1977. and Management (ICISTM'09), March 2009, pp. 345-346. Springer Berlin Heidelberg [4] T. E. Lindquist, and J. R. Jenkins, ―Test-case generation with IOGen, IEEE Software,‖ vol. 5, no. 1, pp. 72-79, 1988. [25] K. Li, Z. Zhang, and W. Liu, ―Automatic Test Data Generation Based On Ant Colony Optimization,‖ Proc. of Fifth International Conference [5] R. Ferguson and B. Korel, ―The chaining approach for software test data on Natural Computationn 2009, pp. 216-219. IEEE Press. generation,‖ ACM TOSEM, vol. 5, pp. 63-86, 1996. [26] P. R. Srivastava, K. Baby, and G Raghurama, ―An Approach of Optimal [6] B. Korel, ―Automated software test data generation,‖ IEEE Trans. on Path Generation using Ant Colony Optimization,‖ Proc. of TENCON Software Engineering, vol. 16, pp. 870-879, 1990. 2009, pp.1-6. IEEE Press. [7] M. Harman, "The current state and future of search based software [27] M. Dorigo and C. Blum ―Ant colony optimization theory: A survey‖, engineering," Proc. of the International Conference on Future of Theoretical Computer Science, 344(2-3), pp. 243-278, 2005. Software Engineering (FOSE'07), May 2007, pp. 342-357. IEEE Press. [28] P. G. Frankl, and E. J. Weyuker, ―An Applicable Family of Data Flow [8] R. P. Pargas, M. J. Harrold, and R. R. Peck, ―Test data generation using Testing Criteria,‖ IEEE Transactions on Software Engineering, vol. 14, genetic algorithms, Journal of Software Testing,‖ Verifications, and 1988, no. 10, pp. 1483-1498. Reliability, vol. 9, pp. 263-282, 1999. [29] S. Rapps and E.J. Weyuker, ―Selecting software test data using data flow [9] A. S. Ghiduk, M. J. Harrold, M. R. Girgis, ―Using genetic algorithms to information,‖ IEEE Transactions on Software Engineering, vol.11, no. 4, aid test-data generation for data flow coverage,‖ Proc. of 14th Asia- pp. 367-375, 1985. Pacific Software Engineering Conference (APSEC 07), Dec. 2007, pp. 41-48. IEEE Press. [30] M.R. Girgis and M.R. Woodward, ―An integrated system for program testing using weak mutation and data flow analysis,‖ Proceedings of [10] C. C. Michael, G. E. McGraw, M. A. Schatz, ―Generating software test Eighth International Conference on Software Engineering, IEEE data by evolution,‖ IEEE Transactions on Software Engineering, vol.27, Computer Society, pp. 313-319, 1985. no.12, pp. 1085-1110, 2001. [31] F. E. Allen and J. Cocke, ―A program data flow analysis procedure,‖ [11] J. Wegener, A. Baresel, H. Sthamer, ―Evolutionary test environment for Communication of the ACM, 19 (3), 137-147, 1976. automatic structural testing,‖ Journal of Information and Software Technology, vol. 43, pp. 841-854, 2001. [12] L. Bottaci, ―A genetic algorithm fitness function for mutation testing,‖ Ahmed S. Ghiduk is an assistant professor at Beni-Suef University, Egypt. Seminal: Software Engineering Using Metaheuristic Innovative He received the BSc degree from Cairo University, Egypt, in 1994, the MSc Algorithms, 2001. degree from Minia University, Egypt, in 2001, and a Ph.D. from Beni-Suef University, Egypt in joint with College of Computing, Georgia Institute of [13] M. R. Girgis, ―Automatic test data generation for data flow testing using Technology, USA, in 2007. His research interests include software a genetic algorithm,‖ Journal of Universal computer Science, vol. 11, no. engineering especially search-based software testing, genetic algorithms, and 5, pp. 898-915, 2005. ant colony. Currently, Ahmed S. Ghiduk is an assistant professor at College of [14] M. Dorigo, V. Maniezzo, and A. Colorni, ―Ant System: Optimization by Computers and Information Systems, Taif University, Saudi Arabia. One can a Colony of Cooperating Agents,‖ IEEE Transactions on Systems, Man, connect Ahmed S. Ghiduk on firstname.lastname@example.com or gamil.com. and Cybernetics-Part B Cybernetics, vol. 26, no. 1, pp. 29-41, 1996. [15] C. Blum, ―Ant colony optimization: introduction and hybridizations‖ Proc. of 7th International Conference on Hybrid Intelligent Systems (HIS'07), Sept. 2007, pp. 24-29. IEEE Press. [16] X. Zhang, H. Meng, and L. Jiao, ―Intelligent particle swarm optimization in multiobjective optimization,‖ Proc. of the 2005 IEEE Congress on Evolutionary Computation, Vo. 1, pp. 714-719. IEEE Press. [17] D.T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, and M. Zaidi ―The bees algorithm – A novel tool for complex optimisation problems‖ Proc. of Innovative Production Machines and Systems Conference (IPROMS'06), 2006, pp.454-461. 72
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It would not be outrageous to suggest the Pirates are a team without a weakness.
Calipari's success deserves the acclaim he has been getting, but there are issues that cannot be ignored.
The long-term contract, announced more than three years ago, has not been what it was expected to be.
There are two ways to look at the Penguins performance Thursday night against the Carolina Hurricanes:
With opening day less than two weeks away, Pirates manager Clint Hurdle will show what likely will be the team's regular lineup.
Nobody asked me, but . . .
Call this Charlie Morton Appreciation Day. Which is only fitting since yesterday was Rip Charlie Morton Day.
Random thoughts after 68 hours in Bradenton, Fla.
It's been the most quiet Pirates spring training in memory.
The Pirates success continues to grow.
Selected short subjects:
Nobody asked me, but . . .
By almost every measure, it's been a good spring training for the Pirates.
The importance of having an elite quarterback is the NFL's answer to the massive revenue of the Yankees/Red Sox/Dodgers/Cubs.
Building an MLB roster is far more nuanced work than it might appear to be.
The Steelers, who seemed content to see how things played out before pursuing Harrison, might need to be more proactive.
Nobody asked me, but . . .
Hall of Fame owner/manager/player Connie Mack, legend has it, once said, ''Pitching is 75 percent of baseball.
About two weeks ago, this site posted, the five biggest Pirates question marks for the 2015 season.
Barring a semi-major miracle, the Pitt basketball team is headed to the NIT.
It's a well-known fact that in too many cases outstanding professional athletes do not easily walk away from the job.
In terms of the MLB landscape, Andrew McCutchen is not quite a once-in-a-generation player.
Nobody asked me, but . . .
Pittsburgh's two most popular winter sports teams are moving in opposite directions.
A caller to the 'Bob Pompeani Show' Saturday proclaimed that Pirates shortstop Jordy Mercer would be under 'a lot of pressure,' during
The opening faceoff at the Consol Energy Center tonight is shortly after 5 p.m. The opening tipoff for Pitt at Wake Forest basketball is
There has been a lot of recent talk about the possibility of the Pirates offering contract extensions to Neil Walker and Andrew McCutchen.


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Much like the 1970s punk rock scene belonged to New York and Los Angeles was the birthplace of 1950s film noir, no locale is more synonymous with Modernism than Paris. Aspiring and established artists alike flocked from around the world to access the creative energy.
Located on a sprawling campus, which includes the Ararat Home, a retirement community, an assisted living facility, a church and even a banquet hall, the museum has a fine collection of artifacts not only of the Armenian genocide but also of the history of the Armenian people.
On March 24, at the inaugural exhibition of YARAT Contemporary Art Space in Baku, Azerbaijan, visitors will undoubtedly cluster in front of a grand series of black-and-white portraits, rendered with fine ink and stark contrast. In them: the faces of their fellow Azeri countrymen.
In short, these are instruments meant for the cultivation of a delicate, refined beauty, the sort which may seem difficult to come by in today's loud and fast-paced world, but whose quiet existence is there, inviting us all to consider its "alternate future."
This is a ballet to which I would take anyone who is new to the art form. Most of the dancing takes place in the sun-filled village square into which Don Quixote and Sancho Panza wander, on a (live) horse and mule, in their quest for adventures in chivalry.
As many of my consulting clients seek to move in new directions, I am increasingly involved in helping arts organizations select their leaders. This has forced me to consider what characteristics are essential for a strong arts leader.
Artists and adults at large need to think about how to engage young people in important questions and messy content in a developmentally-appropriate way. But we also should help youth think critically and arrive at their own conclusions. And we must address content that is relevant to their lives and addresses youth perspectives.
It is so odd to feel like an outsider on an issue that touched my life so profoundly and was at least a part of what Arthur Mitchell set out to address 46 years ago when he and Karel Shook cofounded The Dance Theatre of Harlem in the basement of a church in Harlem.
Though seemingly disorganized, Serenity Gathering managed to put together a beautiful festival in spite of oversold tickets and overworked staff. From the eyes of attendees, it was nothing but beautiful music, art, performances and oak trees.
Perhaps the most recognizable poster created by Paul Rand is the one he made for IBM, with its clean iconic triad, the eye, the bee, with the alphabet letter M, striped to match the body of the bee, to complete the rhebus.
Producing a photograph every day was and is hard. It forced us to be creative and get the best out of every day and situation. More than ever it made us realise the beauty that is all around us, and that even with a simple camera you can get beautiful pictures on a boring day.
The best of these have the capacity to transmit the magical healing property of painting -- the feeling that in making them the artist was transformed and that in looking the viewer can be transformed.
Electro-shamanic duo, Lulacruza (Luis Maurette and Alejandra Ortiz), are beautifying the sonic world with their earthly sounds and profound lyricism. A perfect blend of electronic and acoustic, the music of Lulacruza encompasses the spirit of humans, animals and nature.
The result of the Met's new production of Tchaikovsky's Iolanta paired with Bartok's Bluebeard's Castle was an evening as inert as the snow that blanketed Lincoln Center.
Relationships are complex and there's something almost appealing about the self-sufficiency that the universe of masturbation provides.
Give Wendy Wasserstein credit: Her play The Heidi Chronicles brilliantly toes the line between remaining relevant to new, contemporary audiences while simultaneously exemplifying how far we've come from tumultuous years of inequality for women.
In the first of our 'quick 5' interview series, we catch up with seminal Japanese artist Yayoi Kusama, about her work, her wardrobe and last night's dinner.
Jesus arrives as a gay man of today in a modern city with "The Passion of Christ: A Gay Vision," a controversial series of paintings. The paintings and the new book that I wrote about them have been attacked as blasphemy by conservative Christians. But we refuse to concede Jesus to those who act like they own the copyright on Christ, then use him as a weapon to dominate others.


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Mortgage Decision Mini-Case #4 Travis May and Adam September 5, 2002 Introduction Taking out a mortgage of this size is a big decision and gives room to spend thousands of dollars that did not necessarily have to be spent. Decisions on how to pay a 30-year mortgage off can literally mean tens of thousands of dollars in finance charges. In light of the importance about the decision, we had to make a few assumptions before digging in. Assumptions First, we assumed that the loan would be sold to a corporation like Fannie Mae or Freddie Mac to be able to get a rate of 5.75% (fanniemae.com, freddimac.com). This, therefore would be a fixed rate note and all payments must be paid at the back-end of the note (Wilson). Second, we assumed that they purchased term insurance for at least the amount of the house to cover their assets if there was a death (Wilson). Third, we assumed that up to 3 payments a year could be made over and above the normal schedule of payments without hindering their current budget. Definitions There are some terms that may be confusing to the person without a financial background. This section gives clarification to terms that may be difficult to understand. Back End of Note: Payment made that does not roll a due date, the next payment must be made at originally scheduled time. Finance Charges: Cost of interest from taking out a loan, where the bank makes a profit CD: Initials for "Certificate of Deposit"; money deposited that will lock in a return from interest if kept deposited for a specific amount of time. Mortgage Loan: Money borrowed that will be paid off in a specific amount of time in installments at specified times, usually charges an interest rate on money borrowed. Home Equity Loan: Money that can be borrowed against the money that has already been paid into an original Mortgage loan for a house. Up to 80% of the appraised amount of property may be borrowed (Wilson). Sources Used In the pursuit of solving this case, bankrate.com, fanniemae.com, and freddiemac.com were used in figuring rates for loans, savings deposits and CD's. Another source that was used was David Wilson, Senior Vice President and Commercial Loan Officer of Longview Bank & Trust Co. Through Mr. Wilson's practical knowledge about this subject, and the facts from the three web sites, a very informed, and hopefully wise, decision was made. Questions to Be Answered To solve this problem, the following questions must be answered: 1. How many years can I cut off my note by paying one, two, and three payments extra each year? 2. What if the customer does not know if they can afford to make extra payments? 3. What are some alternatives and would they be beneficial? Solutions to Case Below is a chart that depicts how many years it will take to payoff this loan with one, two, and three payments being made above the normal payments during a year. It also gives an approximate value of money saved in finance charges by doing this. Approximate Figures for Early Payoff No Extra 1 Extra 2 Extra 3 Extra Payments Payment Payments Payments Time to Payoff 30 Years 25 Years * 21 1/2 Years 19 Years Interest Saved $ - $ 11,666.70 $ 23,333.40 $ 35,000.10 * Rounded Obviously, paying the most extra payments would payoff the loan the quickest. If the customer does not know if they can fit the extra payments into their budget, it would probably be a safe bet to not put that money in. However, a home equity loan may be taken out on the house. With a down payment of $80,000 given up front, this gives you the equity and allows some breathing room. With this cushion, the risk in paying extra is cut down considerably. There is at least one alternative. One could take out a CD and put money into it hoping to gain the interest money for paying off the note early. However, as shown on the last page, CD rates are lower than the interest rate on the loan (bankrate.com). With the home equity loans that are now in place, paying into your loan would be a better investment because of the higher interest rate and the fact that you can get that money back almost as easy as you can get the money back from a CD. Another alternative would be to invest that money into the stock market or into bonds. However, with age being somewhat of a factor, and with the market in the volatile stage that it is in, this could prove to be disastrous in the future. The risk is great but the return is high. Decision We have decided that that the best way for this customer to pay of f the note would be to add three or more payments per year. This will allow them to save $35,000 in finance charges, cut seven and one half years off their mortgage payout, and the money paid in is still accessible through a home equity loan if they ever got into a bind. This, however, must be reevaluated from time to time. With interest rates constantly changing, the return on investment in the different areas discussed above may be higher down the road. This customer is at an advantage if the rate is fixed at this relatively low interest rate. If they continue to be diligent in paying down the note, they will have many options in the future.
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I had a steak and vegetable dish with macadamia nuts which was one of the best Chinese dinners I have ever had. This place is expensive by US standards for Chinese food - but the quality more than makes up for it.
The food the rest of my family got was better than average but nothing as good as what I ordered. The service was INCREDIBLY slow - which would be my only real complaint, but they were very busy.
Really pretty view and sitting on the river was really nice.
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5 / 5


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George Hicks Jr.: St. Louis Homicide No. 36; Murdered in Holly Hills Sunday Night
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@ Truth, I find it amazing that after four hundred years of slavery, the African American race still poses as the greatest threat in the minds of so many white people like yourself. The commentary on your part in this newsletter is not only disrespectful, but it just shows how far behind your own race is if you all are still thinking about how to destroy the minority. In fact, if it wasn't for the MINORITY, this here "MADE UP AMERICA" would be pure land. You are one out of billions who don't care for the African American race, but if you want someone to blame for us being here, then blame your own ancestors for not being independent enough or efficient enough to build this here "MADE UP AMERICA" own their own. Notice that one: We are labeled as the, "Minority", which means little to nothing. If we are so much of nothing, then why be so paranoid because of our NEVER DYING EXISTENCE! Two: Where did black people come from, oh yeah that's right- WE CAME FROM AFRICA, but on every application, birth certificate and every history book we are identified as "AFRICAN AMERICAN". Now where would we get a name like that, oh yeah AMERICA! I could call you a racist prick or racist bastard for that matter, but instead I'm going to pray for sick mind and hope that your sins will be forgiven. Oh and that black bastard that was murdered was my cousin, so if you ever disrespect the memory of his name again, I'll have your ip addressed track and I'll have your sorry and scary ass arrested for such racist slurs!
(filling my lungs) The air smells a teensy bit cleaner already.
Yall dnt kno George so shake moe
That was my little cousin im so sad I love you cuzz im gonna miss seeing you who ever did this you gonna get yours I cant believe this bull one one g from yo big cuzz little sam
Racist people real tuff on these comment blogs... I'ma pray for them cause its are breast milk runnin through they veins
East St. Louis - check. North St. Louis - check. Next area on this list for these black bastards to destroy...South City.
We be on the lookout for White Supremacists that "kilt hiz ass"
Paul, the address listed is in the Carondelet neighborhood, not Holly Hills.
Violence begets violence. Someone has to break the circle!
nahh. The murder rate is waaay down this year. This time last year, we were at 50, now we're at 36. The number of murders went down from 2010-2011, and it's very likely that it will go down from 2011-2012. The city is getting better, you're just paranoid
What city that they live in haven't they destroyed? That would be the short list.
^^^ fucc you cracca
What? What? What?
What? Sad commentary!
The Truth hurt, don't it Boy?


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