On clustering based aspect mining

Abstract

Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify crosscutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming in order to make them easier to maintain and to evolve. The aim of this paper is to comparatively analyze and evaluate the results obtained by different clustering algorithms in aspect mining. The evaluation is performed on an open source case study using four measures.