Program restructuring is a key method for improving the quality of ill-structured programs, thereby increasing the understandability and reducing the maintenance cost. It is a challenging task and a great deal of research is still ongoing. This paper presents an approach to program restructuring inside of a function based on clustering techniques with cohesion as the major concern. Clustering has been widely used to group related entities together. The approach focuses on automated support for identifying ill-structured or low-cohesive functions and providing heuristic advice in both the development and evolution phases. A new similarity measure is defined and studied intensively specifically from the function perspective. A comparative study on three different hierarchical agglomerative clustering algorithms is also conducted. The best algorithm is applied to restructuring of functions of a real industrial system. The empirical observations show that the heuristic advice provided by the approach can help software designers make better decision of why and how to restructure a program. Specific source code level software metrics are presented to demonstrate the value of the approach.

Journal of Systems and Software
Department of Systems and Computer Engineering

Lung, C.H, Xu, X. (Xia), Zaman, M. (Marzia), & Srinivasan, A. (Anand). (2006). Program restructuring using clustering techniques. Journal of Systems and Software, 79(9), 1261–1279. doi:10.1016/j.jss.2006.02.037