A systematic review on mining techniques for crosscutting concerns
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Aspect mining is a technique that decouples the crosscutting concerns from existing software systems. The goal of aspect mining is to refactor the existing software systems with Aspect Oriented Programming technology. Inspired by the link analysis of information retrieval technology, this paper describes a two-state model to approximate how crosscutting concerns can be discovered in the concern graphs extracted from programs. Our mining algorithm generates ”scatter” and ”centralization” of each program element for the final ranking. The convergency of the algorithm proves fast. The Ranking technique, considering both ”scatter” and ”centralization”, produces a final ranking for identifying crosscutting concerns. Our aspect mining approach is evaluated on numerous Java programs that are of the typical selections for aspect mining. Compared with existing aspect mining approaches, our mining approach captures more information that helps domain experts refactor software systems and prove effective in identifying crosscutting concerns.