An empirical comparison of dynamic impact analysis algorithms

Abstract

Impact analysis - determining the potential effects of changes on a software system - plays an important role in software engineering tasks such as maintenance, regression testing, and debugging. In previous work, two new dynamic impact analysis techniques, CoverageImpact and PathImpact, were presented. These techniques perform impact analysis based on data gathered about program behavior relative to specific inputs, such as inputs gathered from field data, operational profile data, or test-suite executions. Due to various characteristics of the algorithms they employ, CoverageImpact and PathImpact are expected to differ in terms of cost and precision; however, there have been no studies to date examining the extent to which such differences may emerge in practice. Since cost-precision tradeoffs may play an important role in technique selection and further research, we wished to examine these tradeoffs. We therefore designed and performed an empirical study, comparing the execution and space costs of the techniques, as well as the precisions of the impact analysis results that they report. This paper presents the results of this study.