Extending Dynamic Aspect Mining Using Formal Concept Analysis

Authors:
Liping Qu;Daxin Liu
Affiliations:
Harbin Engineering University, Harbin 150001, China;Harbin Engineering University, Harbin 150001, China
Venue:
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
Year:
2007

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Abstract

The fact that crosscutting concerns cannot be well modularized in object-oriented software is an impediment to program comprehension: the implementation of a concern is typically scattered over many locations and tangled with the implementation of other concerns, resulting in a system that is hard to explore and understand. Aspect mining aims to identify crosscutting concerns in a system, thereby improving the system's comprehensibility and enabling migration of existing (object-oriented) programs to aspect-oriented ones. In this paper, we briefly introduce DynAMiT, a dynamic aspect mining tool that detects crosscutting concerns based on tracing method executions. While the approach is generally fairly precise, further analysis revealed that some aspect candidates were blurred or not detected. We enhanced the mining capabilities of DynAMiT by using formal concept analysis.