Automated software remodularization based on move refactoring: a complex systems approach

Abstract

Modular design is a desirable characteristic of complex software systems that can significantly improve their comprehensibility, maintainability and thus quality. While many software systems are initially created in a modular way, over time modularity typically degrades as components are reused outside the context where they were created. In this paper, we propose an automated strategy to remodularize software based on move refactoring, i.e. moving classes between packages without changing any other aspect of the source code. Taking a complex systems perspective, our approach is based on complex networks theory applied to the dynamics of software modular structures and its relation to an n-state spin model known as the Potts Model. In our approach, nodes are probabilistically moved between modules with a probability that nonlinearly depends on the number and module membership of their adjacent neighbors, which are defined by the underlying network of software dependencies. To validate our method, we apply it to a dataset of 39 Java open source projects in order to optimize their modularity. Comparing the source code generated by the developers with the optimized code resulting from our approach, we find that modularity (i.e. quantified in terms of a standard measure from the study of complex networks) improves on average by 166+-77 percent. In order to facilitate the application of our method in practical studies, we provide a freely available Eclipse plug-in.