Practical Isolation of Failure-Inducing Changes for Debugging Regression Faults

During software evolution, new released versions still contain many bugs. One common scenario is that end users encounter regression faults and submit them to bug tracking systems. Different from in-house regression testing, typically only one test input is available, which passes the old version and fails the modified new version. To address the issue, delta debugging has been proposed for failure-inducing changes identification between two versions. Despite promising results, there are two practical factors that thwart the application of delta debugging: a large number of tests and misleading false positives. In this work, we present a combination of coverage analysis and delta debugging that automatically isolates failure-inducing changes. Evaluations on twelve real regression faults in GNU software demonstrate both the speed gain and effectiveness improvements. Moreover, a case study on libPNG and TCPflow indicates that our technique is comparable to peer techniques in debugging regressions faults.