You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
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.

Cited Abstract(s):
[1]: Reverse engineering is the process of uncovering the design and the design rationale from a functioning software system. Reverse engineering is an integral part of any successful software system, because changing requirements lead to implementations that drift from their original design. In contrast to traditional reverse engineering techniques ---which analyse a single snapshot of a system--- we focus the reverse engineering effort by determining where the implementation has changed. Since changes of object-oriented software are often phrased in terms of refactorings, we propose a set of heuristics for detecting refactorings by applying lightweight, object-oriented metrics to successive versions of a software system. We validate our approach with three separate case studies of mature object-oriented software systems for which multiple versions are available. The case studies suggest that the heuristics support the reverse engineering process by focusing attention on the relevant parts of a software system.
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 [1] , 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.