Revealing code change propagation channels by evolution history mining

Changes on source code may propagate to distant code entities through various kinds of relationships, which may form up change propagation channels. It is however difficult for developers to reveal code change propagate channels due to sophisticated interrelationships among code entities. In this work, we propose a novel graph representation for the changed code entities and related code entities changed within a range of space and time so that the types of relationships along which the changes are propagated can be explicitly presented. Then a subgraph mining technique is used to find the frequent change propagation channels. We finally reveal 40 types of frequent change propagation channels that cover over 98% cases of code change propagation in five well-known open-source Java projects.We find evidence that the code changes propagated through an unchanged intermediate code entity consume more time than those through a changed one, indicating the difficulties in maintaining code entities that related through indirect relationships. We find that a small proportion of code entities frequently appear in the FCPCs, and confirm the semantic relationships between code entities covered by 50 instances of FCPCs, indicating potential usefulness for developers to explain the range of change impact from given source code changes.