Towards Boosting Patch Execution On-the-Fly

Samuel Benton1; Yuntong Xie2; Lan Lu3; Mengshi Zhang4; Xia Li5; Lingming Zhang6

10.1145/3510003.3510117

2022

ACM/IEEE 44th International Conference on Software Engineering (ICSE)

0270-5257

978-1-6654-9589-9

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)

2022-May

2165-2176

25-27 May 2022

Pittsburgh, PA, USA

10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA

IEEE COMPUTER SOC

Program repair is an integral part of every software system's life-cycle but can be extremely challenging. To date, various automated program repair (APR) techniques have been proposed to reduce manual debugging efforts. However, given a real-world buggy program, a typical APR technique can generate a large number of patches, each of which needs to be validated against the original test suite, incurring extremely high computation costs. Although existing APR techniques have already leveraged various static and/or dynamic information to find the desired patches faster, they are still rather costly. In this work, we propose SeAPR (Self-Boosted Automated Program Repair), the first general-purpose technique to leverage the earlier patch execution information during APR to directly boost existing APR techniques themselves on-the-fly. Our basic intuition is that patches similar to earlier high-quality/lowquality patches should be promoted/degraded to speed up the detection of the desired patches. The experimental study on 13 state-of-the-art APR tools demonstrates that, overall, SeAPR can substantially reduce the number of patch executions with negligible overhead. Our study also investigates the impact of various configurations on SeAPR. Lastly, our study demonstrates that SeAPR can even leverage the historical patch execution information from other APR tools for the same buggy program to further boost the current APR tool.

Costs Manuals Debugging Maintenance engineering Benchmark testing Boosting Software

其他

英语

CPCI-S ; EI

National Science Foundation["CCF-2131943","CCF-2141474"]

Computer Science

Computer Science, Software Engineering ; Computer Science, Theory & Methods

WOS:000832185400175

20222812334124

Life cycle ; Program debugging ; Repair

Computer Programming:723.1 ; Computer Applications:723.5 ; Maintenance:913.5

Web of Science

1.University of Texas at Dallas
2.Tsinghua University
3.Southern University of Science and Technology
4.Meta Platforms, Inc.
5.Kennesaw State University
6.University of Illinois at Urbana-Champaign

Samuel Benton,Yuntong Xie,Lan Lu,et al. Towards Boosting Patch Execution On-the-Fly[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:IEEE COMPUTER SOC,2022:2165-2176.