Comparison of similarity metrics for refactoring detection

  • Authors:

  • Benjamin Biegel;Quinten David Soetens;Willi Hornig;Stephan Diehl;Serge Demeyer

  • Affiliations:

  • University of Trier, Germany, Germany;University of Antwerp, Belgium, Belgium;University of Trier, Germany, Germany;University of Trier, Germany, Germany;University of Antwerp, Belgium, Belgium

  • Venue:
  • Proceedings of the 8th Working Conference on Mining Software Repositories
  • Year:
  • 2011

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Abstract

Identifying refactorings in software archives has been an active research topic in the last decade, mainly because it is a prerequisite for various software evolution analyses (e.g., error detection, capturing intent of change, capturing and replaying changes, and relating refactorings and software metrics). Many of these techniques rely on similarity measures to identify structurally equivalent code, however, up until now the effect of this similarity measure on the performance of the refactoring identification algorithm is largely unexplored. In this paper we replicate a well-known experiment from Weißgerber and Diehl, plugging in three different similarity measures (text-based, AST-based, token-based). We look at the overlap of the results obtained by the different metrics, and we compare the results using recall and the computation time. We conclude that the different result sets have a large overlap and that the three metrics perform with a comparable quality.