Improving the detection accuracy of evolutionary coupling by measuring change correspondence

If two or more program entities change together (i.e., co-change) frequently (i.e., in many commits) during software evolution, it is likely that the entities are related and we say that the entities are showing evolutionary coupling. Association rules have been used to express evolutionary coupling and two related measures, support and confidence, have been used to measure the strength of coupling among the co-changed entities. However, an association rule relies only on the number of times the entities have co-changed. It does not analyze whether the changes are corresponding and whether the entities are really related. As a result, association rule often reports false positives and also, ignores important coupling among the infrequently co-changed entities. Focusing on this issue we propose to calculate a new measure, change correspondence, blending the idea of concept location in a code-base to determine whether the changes to the co-changed entities are corresponding and thus, whether they are really related. Our preliminary investigation result on four subject systems written in two programming languages shows that change correspondence has the potential to accurately determine whether two entities are related even if they co-changed infrequently. Thus, we believe that our new measure will help us improve the detection accuracy of evolutionary coupling.