Evaluation Measures for Partitioning based Aspect Mining Techniques

Abstract

Aspect mining is a research direction that tries to identify crosscutting concerns in already developed software systems, without using aspect oriented programming. The goal is to identify them and then to refactor them to aspects, to achieve a system that can be easily understood, maintained and modified. In this paper we propose two new evaluation measures for evaluating the results of partitioning based aspect mining techniques. A small example on how to compute them is provided. The applicability of these measures to different aspect mining techniques is also discussed.