Issue No. 02 - March/April (2011 vol. 37)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TSE.2010.26
Kata Praditwong , The University of Birmingham, Birmingham
Mark Harman , University College London, London
Xin Yao , The University of Birmingham, Birmingham
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.
SBSE, module clustering, multi-objective optimization, evolutionary computation.
M. Harman, X. Yao and K. Praditwong, "Software Module Clustering as a Multi-Objective Search Problem," in IEEE Transactions on Software Engineering, vol. 37, no. , pp. 264-282, 2010.