An analysis of the effects of composite objectives in multiobjective software module clustering

  • Authors:
  • Marcio de Oliveira Barros

  • Affiliations:
  • UNIRIO, Rio de Janeiro, Brazil

  • Venue:
  • Proceedings of the 14th annual conference on Genetic and evolutionary computation
  • Year:
  • 2012

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Abstract

The application of multiobjective optimization to address Software Engineering problems is a growing trend. Multiobjective algorithms provide a balance between the ability of the computer to search a large solution space for valuable solutions and the capacity of the human decision-maker to select an alternative when two or more incomparable objectives are presented. However, when more than a single objective is available, the set of objectives to be considered by the search becomes part of the decision. In this paper, we address the efficiency and effectiveness of using two composite objectives while searching solutions for the software clustering problem. We designed an experimental study which shows that a multiobjective genetic algorithm can find a set of solutions with increased quality and using less processing time if these composite objectives are suppressed from the formulation for the software clustering problem.