A new genetic clustering based approach in aspect mining

Authors:
Gabriela Şerban;Grigoreta S. Moldovan
Affiliations:
Babeş-Bolyai University, Department of Computer Science, Cluj-Napoca, Romania;Babeş-Bolyai University, Department of Computer Science, Cluj-Napoca, Romania
Venue:
MMACTEE'06 Proceedings of the 8th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
Year:
2006

Citing 7
Cited 0

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Abstract

Clustering is a division of data into groups of similar objects. Aspect mining is a process that tries to identify crosscutting concerns in existing software systems. The goal is to refactor the existing systems to use aspect oriented programming, in order to make them easier to maintain and to evolve. This paper aims at presenting a new genetic clustering based approach in aspect mining. Clustering is used in order to identify crosscutting concerns. We evaluate the obtained results from the aspect mining point of view based on two new quality measures. The proposed approach is compared with another clustering approach in aspect mining ([1]) and a case study is also reported.