Comparing and combining genetic and clustering algorithms for software component identification from object-oriented code

Authors:
Selim Kebir;Abdelhak-Djamel Seriai;Allaoua Chaoui;Sylvain Chardigny
Affiliations:
LIRMM, University of Monptellier, France;LIRMM, University of Monptellier, France;University of Constantine, Algeria;MGPS, Port-Saint-Louis, France
Venue:
Proceedings of the Fifth International C* Conference on Computer Science and Software Engineering
Year:
2012

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Abstract

Software component identification is one of the primary challenges in component based software engineering. Typically, the identification is done by analyzing existing software artifacts. When considering object-oriented systems, many approaches have been proposed to deal with this issue by identifying a component as a strongly related set of classes. We propose in this paper a comparison between the formulations and the results of two algorithms for the identification of software components: clustering and genetic. Our goal is to show that each of them has advantages and disadvantages. Thus, the solution we adopted is to combine them to enhance the results.