Hierarchical clustering for adaptive refactorings identification

This paper studies an adaptive refactoring problem. It is well-known that improving the software systems design through refactoring is one of the most important issues during the evolution of object oriented software systems. We focus on identifying the refactorings needed in order to improve the class structure of a software systems, in an adaptive manner, when new application classes are added to the system. We propose an adaptive clustering method based on an hierarchical agglomerative approach, that adjusts the structure of the system that was established by applying a hierarchical agglomerative clustering algorithm before the application classes set changed. The adaptive method identifies, more efficiently, the refactorings that would improve the structure of the extended software system, without decreasing the accuracy of the obtained results. An experiment testing the method's efficiency is also reported.