research-article

The strength of random search on automated program repair

Authors:

Chengsong WangAuthors Info & Claims

ICSE 2014: Proceedings of the 36th International Conference on Software Engineering

Pages 254 - 265

https://doi.org/10.1145/2568225.2568254

Published: 31 May 2014 Publication History

Abstract

Automated program repair recently received considerable attentions, and many techniques on this research area have been proposed. Among them, two genetic-programming-based techniques, GenProg and Par, have shown the promising results. In particular, GenProg has been used as the baseline technique to check the repair effectiveness of new techniques in much literature. Although GenProg and Par have shown their strong ability of fixing real-life bugs in nontrivial programs, to what extent GenProg and Par can benefit from genetic programming, used by them to guide the patch search process, is still unknown.

To address the question, we present a new automated repair technique using random search, which is commonly considered much simpler than genetic programming, and implement a prototype tool called RSRepair. Experiment on 7 programs with 24 versions shipping with real-life bugs suggests that RSRepair, in most cases (23/24), outperforms GenProg in terms of both repair effectiveness (requiring fewer patch trials) and efficiency (requiring fewer test case executions), justifying the stronger strength of random search over genetic programming. According to experimental results, we suggest that every proposed technique using optimization algorithm should check its effectiveness by comparing it with random search.

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Cited By

Xing YWang SSun SHe XSun KLi QBalzarotti DXu W(2024)What IF is not enough? fixing null pointer dereference with contextual checkProceedings of the 33rd USENIX Conference on Security Symposium10.5555/3698900.3698977(1367-1382)Online publication date: 14-Aug-2024
https://dl.acm.org/doi/10.5555/3698900.3698977
Fei ZGe JLi CWang TLi YZhang HHuang LLuo B(2024)Patch Correctness Assessment: A SurveyACM Transactions on Software Engineering and Methodology10.1145/370297234:2(1-50)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3702972
Lin BWang SWen MChen LMao XChristakis MPradel M(2024)One Size Does Not Fit All: Multi-granularity Patch Generation for Better Automated Program RepairProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3680381(1554-1566)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3680381
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Index Terms

The strength of random search on automated program repair
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging
  2. Software notations and tools

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cover image ACM Conferences

ICSE 2014: Proceedings of the 36th International Conference on Software Engineering

May 2014

1139 pages

ISBN:9781450327565

DOI:10.1145/2568225

General Chair:
Pankaj Jalote
IIIT-Delhi, India
,
Program Chairs:
Lionel Briand
University of Luxembourg, Luxembourg
,
André van der Hoek
University of California, Irvine, USA

Copyright © 2014 ACM.

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Published: 31 May 2014

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ICSE '14: 36th International Conference on Software Engineering

May 31 - June 7, 2014

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Cited By

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https://dl.acm.org/doi/10.5555/3698900.3698977
Fei ZGe JLi CWang TLi YZhang HHuang LLuo B(2024)Patch Correctness Assessment: A SurveyACM Transactions on Software Engineering and Methodology10.1145/370297234:2(1-50)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3702972
Lin BWang SWen MChen LMao XChristakis MPradel M(2024)One Size Does Not Fit All: Multi-granularity Patch Generation for Better Automated Program RepairProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3680381(1554-1566)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3680381
Ouyang YYang JZhang LChristakis MPradel M(2024)Benchmarking Automated Program Repair: An Extensive Study on Both Real-World and Artificial BugsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652140(440-452)Online publication date: 11-Sep-2024
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Yuan YHuyen PTan SMechtaev SKhurshid S(2024)ARJA-e for the First International Competition on Automated Program RepairProceedings of the 5th ACM/IEEE International Workshop on Automated Program Repair10.1145/3643788.3648019(50-52)Online publication date: 20-Apr-2024
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Zirak AHemmati H(2024)Improving Automated Program Repair with Domain AdaptationACM Transactions on Software Engineering and Methodology10.1145/363197233:3(1-43)Online publication date: 15-Mar-2024
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