earticle

영어

Interesting information and Meta-information about software systems can be extracted by analyzing their evolution histories. This information has been proved useful for understanding software evolution, predicting future changes, and performing an efficient change impact analysis. A rich source code repository is a prerequisite for a high quality evolution analysis. Nonetheless, the evolutionary information contained in current versioning systems for Aspect Oriented (AO) software is incomplete and of low quality, hence limiting the scope of AO software evolution analysis. In spite of AO Programming (AOP) characteristics, none of current versioning tools match the need of controlling and storing the AO software evolution, they do not perform well with obliviousness and quantification found in AO code. In this paper, we suggest a rule-based repository for AO software evolution, and specifically for AspectJ programming language. This repository is dedicated to handle the proper characteristics of AO paradigm. In our proposal changes are formulated as rewriting rules and recorded in the repository when they are applied. Then, this last is analyzed to detect change patterns in AspectJ software evolution. We give here, the details of our rule-based repository, as well as the proposed approach for change pattern detection. We present a tool validation and some experimentation to prove the feasibility and the efficiency of our proposals.