Hey APR! Integrate Our Fault Localization Skill: Toward Better Automated Program Repair

Abstract

Background: Prior studies lack the perspective of using developer's skills to augment the performance of automated program repair (APR). APR has a phase referred to as fault localization (FL), which automatically finds the faulty statement that causes faults. To achieve a well-performed FL phase, we study developers' FL skills, which allow developers to find faulty statements. We suppose that such FL skills can add additional information to fault localization to augment the accuracy of fault localization and reduce the execution cost of APR. Aims: We aim at revealing a criterion that distinguishes whether using the FL skill reduces the execution cost of the state-of-the-art APR, TBar, depending on the accuracy of the FL skill. Method: We conduct a simulation case study in the Defects4J dataset, which is the most popular dataset. We compare the numbers of candidate patches generated by TBar using the FL skill or using spectrum-based fault localization (SBFL). Results: Our case study revealed that, if developers localized the faulty statements before inspecting 40 % of the statements in the target program, the execution cost of TBar reduces for over half of the studied faults. The 40 % value is a requirement for developers using the FL skill to augment the performance of APR. Conclusion: If developers can localize the faulty statement before inspecting 40 % of the statements, integrating the FL skill with SBFL makes TBar faster compared to when SBFL is used.