Modularity is a desirable characteristic for software systems. In this article we propose to use a quantitative method from complex network sciences to estimate the coherence between the modularity of the dependency network of large open source Java projects and their decomposition in terms of Java packages. The results presented in this article indicate that our methodology offers a promising and reasonable quantitative approach with potential impact on software engineering processes.
@cite_5: Software systems emerge from mere keystrokes to form intricate functional networks connecting many collaborating modules, objects, classes, methods, and subroutines. Building on recent advances in the study of complex networks, I have examined software collaboration graphs contained within several open-source software systems, and have found them to reveal scale-free, small-world networks similar to those identified in other technological, sociological, and biological systems. I present several measures of these network topologies, and discuss their relationship to software engineering practices. I also present a simple model of software system evolution based on refactoring processes which captures some of the salient features of the observed systems. Some implications of object-oriented design for questions about network robustness, evolvability, degeneracy, and organization are discussed in the wake of these findings.
@cite_4: “Evolution behaves like a tinkerer” (Francois Jacob, Science, 1977). Software systems provide a singular opportunity to understand biological processes using concepts from network theory. The Debian GNU Linux operating system allows us to explore the evolution of a complex network in a unique way. The modular design detected during its growth is based on the reuse of existing code in order to minimize costs during programming. The increase of modularity experienced by the system over time has not counterbalanced the increase in incompatibilities between software packages within modules. This negative effect is far from being a failure of design. A random process of package installation shows that the higher the modularity, the larger the fraction of packages working properly in a local computer. The decrease in the relative number of conflicts between packages from different modules avoids a failure in the functionality of one package spreading throughout the entire system. Some potential analogies with the evolutionary and ecological processes determining the structure of ecological networks of interacting species are discussed.
For an early attempt of the application of network science to the analysis of software engineering processes we recommend @cite_5 , which also contains a short review of classical approaches used in the software engineering literature. Finally, a recent article published in the journal used a similar network approach, though with a different metric, to study modularity of code and its relation to module survival, drawing a parallel to ecological systems and making use of a predator-prey model variation @cite_4 .