Impact Analysis based on a Global Hierarchical Object Graph

During impact analysis on object-oriented code, statically extracting dependencies is often complicated by subclassing, programming to interfaces, aliasing, and collections, among others. When a tool recommends a large number of types or does not rank its recommendations, it may lead developers to explore more irrelevant code. We propose to mine and rank dependencies based on a global, hierarchical points-to graph that is extracted using abstract interpretation. A previous whole-program static analysis interprets a program enriched with annotations that express hierarchy, and over-approximates all the objects that may be created at runtime and how they may communicate. In this paper, an analysis mines the hierarchy and the edges in the graph to extract and rank dependencies such as the most important classes related to a class, or the most important classes behind an interface. An evaluation using two case studies on two systems totaling 10,000 lines of code and five completed code modification tasks shows that following dependencies based on abstract interpretation achieves higher effectiveness compared to following dependencies extracted from the abstract syntax tree. As a result, developers explore less irrelevant code.