A framework for cost-effective dependence-based dynamic impact analysis

Dynamic impact analysis can greatly assist developers with managing software changes by focusing their attention on the effects of potential changes relative to concrete program executions. While dependence-based dynamic impact analysis (DDIA) provides finer-grained results than traceability-based approaches, traditional DDIA techniques often produce imprecise results, incurring excessive costs thus hindering their adoption in many practical situations. In this paper, we present the design and evaluation of a DDIA framework and its three new instances that offer not only much more precise impact sets but also flexible cost-effectiveness options to meet diverse application needs such as different budgets and levels of detail of results. By exploiting both static dependencies and various dynamic information including method-execution traces, statement coverage, and dynamic points-to data, our techniques achieve that goal at reasonable costs according to our experiment results. Our study also suggests that statement coverage has generally stronger effects on the precision and cost-effectiveness of DDIA than dynamic points-to data.