research-article

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Trust enhancement issues in program repair

Authors:

Ridwan Shariffdeen,

Abhik RoychoudhuryAuthors Info & Claims

ICSE '22: Proceedings of the 44th International Conference on Software Engineering

Pages 2228 - 2240

https://doi.org/10.1145/3510003.3510040

Published: 05 July 2022 Publication History

Abstract

Automated program repair is an emerging technology that seeks to automatically rectify bugs and vulnerabilities using learning, search, and semantic analysis. Trust in automatically generated patches is necessary for achieving greater adoption of program repair. Towards this goal, we survey more than 100 software practitioners to understand the artifacts and setups needed to enhance trust in automatically generated patches. Based on the feedback from the survey on developer preferences, we quantitatively evaluate existing test-suite based program repair tools. We find that they cannot produce high-quality patches within a top-10 ranking and an acceptable time period of 1 hour. The developer feedback from our qualitative study and the observations from our quantitative examination of existing repair tools point to actionable insights to drive program repair research. Specifically, we note that producing repairs within an acceptable time-bound is very much dependent on leveraging an abstract search space representation of a rich enough search space. Moreover, while additional developer inputs are valuable for generating or ranking patches, developers do not seem to be interested in a significant human-in-the-loop interaction.

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Cited By

Kim YPark YHan SYi JFilkov VRay BZhou M(2024)Enhancing the Efficiency of Automated Program Repair via Greybox AnalysisProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695602(1719-1731)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695602
Li GZhi CChen JHan JDeng SFilkov VRay BZhou M(2024)Exploring Parameter-Efficient Fine-Tuning of Large Language Model on Automated Program RepairProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695066(719-731)Online publication date: 27-Oct-2024
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Petke JMartinez MKechagia MAleti ASarro Fd'Amorim M(2024)The Patch Overfitting Problem in Automated Program Repair: Practical Magnitude and a Baseline for Realistic BenchmarkingCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663776(452-456)Online publication date: 10-Jul-2024
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cover image ACM Conferences

ICSE '22: Proceedings of the 44th International Conference on Software Engineering

May 2022

2508 pages

ISBN:9781450392211

DOI:10.1145/3510003

General Chair:
Matthew B Dwyer
University of Virginia
,
Program Chairs:
Daniela Damian
University of Victoria, Canada
,
Andreas Zeller
CISPA, Germany

Copyright © 2022 ACM.

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Published: 05 July 2022

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Cited By

Kim YPark YHan SYi JFilkov VRay BZhou M(2024)Enhancing the Efficiency of Automated Program Repair via Greybox AnalysisProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695602(1719-1731)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695602
Li GZhi CChen JHan JDeng SFilkov VRay BZhou M(2024)Exploring Parameter-Efficient Fine-Tuning of Large Language Model on Automated Program RepairProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695066(719-731)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695066
Petke JMartinez MKechagia MAleti ASarro Fd'Amorim M(2024)The Patch Overfitting Problem in Automated Program Repair: Practical Magnitude and a Baseline for Realistic BenchmarkingCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663776(452-456)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3663529.3663776
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
https://dl.acm.org/doi/10.1145/3650212.3652140
Yabesi SAmini MRistic JSharafi ZBaysal OLinares-Vasquez MMoran KSteinmacher I(2024)Exploring the Effects of Urgency and Reputation in Code Review: An Eye-Tracking StudyProceedings of the 32nd IEEE/ACM International Conference on Program Comprehension10.1145/3643916.3644425(202-213)Online publication date: 15-Apr-2024
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Glock JRoychoudhury APaiva AAbreu RStorey M(2024)Aiding Developer Understanding of Software Changes via Symbolic Execution-based Semantic DifferencingProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3639783(142-144)Online publication date: 14-Apr-2024
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Williams DCallan JKirbas SMechtaev SPetke JPrideaux-Ghee TSarro FRoychoudhury APaiva AAbreu RStorey MAniche MNagappan N(2024)User-Centric Deployment of Automated Program Repair at BloombergProceedings of the 46th International Conference on Software Engineering: Software Engineering in Practice10.1145/3639477.3639756(81-91)Online publication date: 14-Apr-2024
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Meem FSmith JJohnson BRoychoudhury APaiva AAbreu RStorey M(2024)Exploring Experiences with Automated Program Repair in PracticeProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639182(1-11)Online publication date: 20-May-2024
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Eladawy HLe Goues CBrun YRoychoudhury APaiva AAbreu RStorey M(2024)Automated Program Repair, What Is It Good For? Not Absolutely Nothing!Proceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639095(1-13)Online publication date: 20-May-2024
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Ye HMonperrus MRoychoudhury APaiva AAbreu RStorey M(2024)ITER: Iterative Neural Repair for Multi-Location PatchesProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623337(1-13)Online publication date: 20-May-2024
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