Improving Automated Program Repair with Retrospective Fault Localization
Tongtong Xu · 2019
Although being recognized as a critical step in automated program repair, fault localization has been only loosely coupled into the fixing process in existing program repair approaches, in the sense that fault localization has limited interactions with other activities in fixing. We propose in this paper to deeply integrate fault localization into the fixing process to achieve more effective and efficient program repair. Our approach introduces a feedback loop in fixing between the activities for locating the fault causes and those for generating and evaluating candidate fixes. The feedback loop enables partial evaluation results of candidate fixes to be used to locate fault localization more accurately, and eventually leads to fixing processes with improved effectiveness and efficiency. We have implemented the approach into a tool, named RESTORE, based on the JAID program repair system. Experiments involving faults from the DEFECTS4J standard benchmark indicate that the integrated fault localization can boost automated program repair: RESTORE produced valid fixes to 63 faults and correct ones to 38 faults, outperforming any other state-of-the-art repair tool for Java while taking 36% less running time compared with JAID.