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.
Another possible, complementary, reason for fluctuations are refactoring events, where software is usually rewritten or restructured in order to improve multiple features such as functionality, flexibility, reusability or structural quality. Such events could lead to the sudden jumps observed in Figure along the time evolution of a software project. In @cite_13 , refactoring metrics are proposed which take into account the dynamics of changing code. This line of research is well aligned with our purposes and can be easily adapted and augmented by our network perspective on software development processes.
@cite_13
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Software developers often duplicate source code to replicate functionality. This practice can hinder the maintenance of a software project: bugs may arise when two identical code segments are edited inconsistently. This paper presents DejaVu, a highly scalable system for detecting these general syntactic inconsistency bugs. DejaVu operates in two phases. Given a target code base, a parallel inconsistent clone analysis first enumerates all groups of source code fragments that are similar but not identical. Next, an extensible buggy change analysis framework refines these results, separating each group of inconsistent fragments into a fine-grained set of inconsistent changes and classifying each as benign or buggy. On a 75+ million line pre-production commercial code base, DejaVu executed in under five hours and produced a report of over 8,000 potential bugs. Our analysis of a sizable random sample suggests with high likelihood that at this report contains at least 2,000 true bugs and 1,000 code smells. These bugs draw from a diverse class of software defects and are often simple to correct: syntactic inconsistencies both indicate problems and suggest solutions.