API Usage Change Rules Mining based on Fine-grained Call Dependency Analysis

Abstract

Software frameworks are widely used in application development. But APIs of a framework may change when it evolves to accommodate new feature requests or to fix bugs. Those changes may break existing client programs of the framework, so client programs need to be migrated to the updated release when the framework evolves. Some technologies (e.g. call dependency analysis) have been proposed to find replacement APIs between the old and new framework releases. However, existing approaches based on call dependency analysis take whole method body as an analysis unit. The context in which a method is called is ignored. In this paper, we present a fine-grained approach named AUC-Miner to infer API usage change rules between two releases of the framework. To take method invocation context into consideration, we propose an approach to get more precise call relationship changes by code splitting. We also analyze indirect method invocations to re-fine call dependency analysis. After elaborating API usage change transactions, we adopt frequent item-set mining to generate API replacement rules. Text similarity and some heuristics to identify evolution of root methods are also applied in the mining progress. The evaluation of AUC-Miner on three popular frameworks shows that its precision is higher than basic call dependency analysis and another API replacement recommendation tool named AURA.