TY - JOUR
T1 - RESTORE: Retrospective Fault Localization Enhancing Automated Program Repair
AU - Xu, Tongtong
AU - Chen, Liushan
AU - Pei, Yu
AU - Zhang, Tian
AU - Pan, Minxue
AU - Furia, Carlo A.
N1 - Publisher Copyright:
© 1976-2012 IEEE.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Fault localization is a crucial step of automated program repair, because accurately identifying program locations that are most closely implicated with a fault greatly affects the effectiveness of the patching process. An ideal fault localization technique would provide precise information while requiring moderate computational resources—to best support an efficient search for correct fixes. In contrast, most automated program repair tools use standard fault localization techniques—which are not tightly integrated with the overall program repair process, and hence deliver only subpar efficiency. In this paper, we present retrospective fault localization : a novel fault localization technique geared to the requirements of automated program repair. A key idea of retrospective fault localization is to reuse the outcome of failed patch validation to support mutation-based dynamic analysis—providing accurate fault localization information without incurring onerous computational costs. We implemented retrospective fault localization in a tool called Restore —based on the Jaid Java program repair system. Experiments involving faults from the Defects4J standard benchmark indicate that retrospective fault localization can boost automated program repair: Restore efficiently explores a large fix space, delivering state-of-the-art effectiveness (41 Defects4J bugs correctly fixed, 8 of which no other automated repair tool for Java can fix) while simultaneously boosting performance (speedup over 3 compared to Jaid ). Retrospective fault localization is applicable to any automated program repair techniques that rely on fault localization and dynamic validation of patches.
AB - Fault localization is a crucial step of automated program repair, because accurately identifying program locations that are most closely implicated with a fault greatly affects the effectiveness of the patching process. An ideal fault localization technique would provide precise information while requiring moderate computational resources—to best support an efficient search for correct fixes. In contrast, most automated program repair tools use standard fault localization techniques—which are not tightly integrated with the overall program repair process, and hence deliver only subpar efficiency. In this paper, we present retrospective fault localization : a novel fault localization technique geared to the requirements of automated program repair. A key idea of retrospective fault localization is to reuse the outcome of failed patch validation to support mutation-based dynamic analysis—providing accurate fault localization information without incurring onerous computational costs. We implemented retrospective fault localization in a tool called Restore —based on the Jaid Java program repair system. Experiments involving faults from the Defects4J standard benchmark indicate that retrospective fault localization can boost automated program repair: Restore efficiently explores a large fix space, delivering state-of-the-art effectiveness (41 Defects4J bugs correctly fixed, 8 of which no other automated repair tool for Java can fix) while simultaneously boosting performance (speedup over 3 compared to Jaid ). Retrospective fault localization is applicable to any automated program repair techniques that rely on fault localization and dynamic validation of patches.
UR - http://www.scopus.com/inward/record.url?scp=85123191066&partnerID=8YFLogxK
U2 - 10.1109/TSE.2020.2987862
DO - 10.1109/TSE.2020.2987862
M3 - Journal article
SN - 0098-5589
VL - 48
SP - 309
EP - 326
JO - IEEE Transactions on Software Engineering
JF - IEEE Transactions on Software Engineering
IS - 1
ER -