Identifying traits with formal concept analysis

Abstract

Traits are basically mixins or interfaces but with method bodies. In languages that support traits, classes are composed out of traits. There are two main advantages with traits. Firstly, decomposing existing classes into traits from which they can be recomposed improves the factoring of hierarchies. Secondly it increases the library reuse potential by providing more reusable traits. Identifying traits and decomposing class hierarchies into traits is therefore an important and challenging task to facilitate maintainability and evolution. In this paper we present how we use Formal Concept Analysis to identify traits in inheritance hierarchies. Our approach is two-staged: first we identify within a hierarchy maximal groups of methods that have a set of classes in common, second we cluster cohesive groups of methods based on method invocations as potential traits. We applied our approach on two significant hierarchies and compare our results with the manual refactorization of the same code which was done by the authors of traits.