Research Article Open Access

A Comparative Classification of Aspect Mining Approaches

Bounour Nora, Ghoul Said and Atil Fadila

Abstract

In object oriented paradigm, 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. Identifying such code automatically greatly improves both the maintainability and the evolveability of the application. Aspect mining aims to identify crosscutting concerns in existing systems, thereby improving the system's comprehensibility and enabling migration of existing (object-oriented) programs to aspect-oriented ones. Aspect are mined either by use of static information or dynamic information of the code. The purpose of this article is to present a survey of the current techniques of aspect mining. We seek to understand both the strengths and limitations of this new area.

Journal of Computer Science
Volume 2 No. 4, 2006, 322-325

DOI: https://doi.org/10.3844/jcssp.2006.322.325

Submitted On: 12 December 2005 Published On: 30 April 2006

How to Cite: Nora, B., Said, G. & Fadila, A. (2006). A Comparative Classification of Aspect Mining Approaches. Journal of Computer Science, 2(4), 322-325. https://doi.org/10.3844/jcssp.2006.322.325

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Keywords

  • Aspect oriented programming
  • aspect mining
  • crosscutting concern
  • program analysis
  • reverse engineering