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Issue No.02 - March/April (2011 vol.37)
pp: 264-282
Mark Harman , University College London, London
Kata Praditwong , The University of Birmingham, Birmingham
ABSTRACT
Software module clustering is the problem of automatically organizing software units into modules to improve program structure. There has been a great deal of recent interest in search-based formulations of this problem in which module boundaries are identified by automated search, guided by a fitness function that captures the twin objectives of high cohesion and low coupling in a single-objective fitness function. This paper introduces two novel multi-objective formulations of the software module clustering problem, in which several different objectives (including cohesion and coupling) are represented separately. In order to evaluate the effectiveness of the multi-objective approach, a set of experiments was performed on 17 real-world module clustering problems. The results of this empirical study provide strong evidence to support the claim that the multi-objective approach produces significantly better solutions than the existing single-objective approach.
INDEX TERMS
SBSE, module clustering, multi-objective optimization, evolutionary computation.
CITATION
Mark Harman, Kata Praditwong, "Software Module Clustering as a Multi-Objective Search Problem", IEEE Transactions on Software Engineering, vol.37, no. 2, pp. 264-282, March/April 2011, doi:10.1109/TSE.2010.26
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