Comparison of Similarity Metrics for Refactoring Detection

Identifying refactorings in software archives has been an ac- tive 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 re- playing changes, and relating refactorings and software met- rics). 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 unex- plored. In this paper we replicate a well-known experiment from Weißgerber and Diehl, plugging in three different sim- ilarity 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.