Software Module Clustering as a Multi-Objective Search Problem

  • Authors:

  • Kata Praditwong;Mark Harman;Xin Yao

  • Affiliations:

  • The University of Birmingham, Birmingham;University College London, London;The University of Birmingham, Birmingham

  • Venue:
  • IEEE Transactions on Software Engineering
  • Year:
  • 2011

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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.