Pareto optimal search based refactoring at the design level

  • Authors:
  • Mark Harman;Laurence Tratt

  • Affiliations:
  • King's College London, London, United Kingdom;King's College London, London, United Kingdom

  • Venue:
  • Proceedings of the 9th annual conference on Genetic and evolutionary computation
  • Year:
  • 2007

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Abstract

Refactoring aims to improve the quality of a software systems' structure, which tends to degrade as the system evolves. While manually determining useful refactorings can be challenging, search based techniques can automatically discover useful refactorings. Current search based refactoring approaches require metrics to be combined in a complex fashion, and producea single sequence of refactorings. In this paper we show how Pareto optimality can improve search based refactoring, making the combination of metrics easier, and aiding the presentation of multiple sequences of optimal refactorings to users.