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Software change impact analysis (IA) plays a crucial role in software evolution. IA aims at identifying thepossible effects of a source code modification. It is often used to evaluate the effects of a change after itsimplementation. However, more proactive approaches use IA to predict the potential effects of a changebefore it is implemented. In this way, IA provides useful information that can be used, among others, toguide the implementation of the change and to support regression tests selection. This paper aims atproposing a change impact analysis model for AspectJ programs. Aspect-Oriented Programming (AOP) is anatural extension of Object-Oriented Programming (OOP). It particularly promotes improved separation ofcrosscutting concerns into single units called aspects. The IA techniques proposed for object-orientedprograms are not directly applicable for aspect-oriented programs due to the new dependencies introducedby aspects. The proposed model was designed to particularly support predictive IA. The model includesseveral impact rules based on the AspectJ language constructs. We performed an empirical evaluation of themodel using several AspectJ programs. In order to assess the model prediction quality, we used twotraditional measures: precision and recall. The reported results show that the model is able to achieve highaccuracy.

A Change Impact Analysis Model for Aspect Oriented Programs