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Practical Program Repair via Preference-based Ensemble Strategy

Authors:

Tegawende F. Bissyande,

Vincent NgAuthors Info & Claims

ICSE '24: Proceedings of the 46th IEEE/ACM International Conference on Software Engineering

Article No.: 5, Pages 1 - 13

https://doi.org/10.1145/3597503.3623310

Published: 06 February 2024 Publication History

Abstract

To date, over 40 Automated Program Repair (APR) tools have been designed with varying bug-fixing strategies, which have been demonstrated to have complementary performance in terms of being effective for different bug classes. Intuitively, it should be feasible to improve the overall bug-fixing performance of APR via assembling existing tools. Unfortunately, simply invoking all available APR tools for a given bug can result in unacceptable costs on APR execution as well as on patch validation (via expensive testing). Therefore, while assembling existing tools is appealing, it requires an efficient strategy to reconcile the need to fix more bugs and the requirements for practicality. In light of this problem, we propose a Preference-based Ensemble Program Repair framework (P-EPR), which seeks to effectively rank APR tools for repairing different bugs. P-EPR is the first non-learning-based APR ensemble method that is novel in its exploitation of repair patterns as a major source of knowledge for ranking APR tools and its reliance on a dynamic update strategy that enables it to immediately exploit and benefit from newly derived repair results. Experimental results show that P-EPR outperforms existing strategies significantly both in flexibility and effectiveness.

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Cited By

Huang KXu ZYang SSun HLi XYan ZZhang Y(2024)Evolving Paradigms in Automated Program Repair: Taxonomy, Challenges, and OpportunitiesACM Computing Surveys10.1145/369645057:2(1-43)Online publication date: 10-Oct-2024
https://dl.acm.org/doi/10.1145/3696450
Xin QWu HTang JLiu XReiss SXuan J(2024)Detecting, Creating, Repairing, and Understanding Indivisible Multi-Hunk BugsProceedings of the ACM on Software Engineering10.1145/36608281:FSE(2747-2770)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3660828

Index Terms

Practical Program Repair via Preference-based Ensemble Strategy
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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cover image ACM Conferences

ICSE '24: Proceedings of the IEEE/ACM 46th International Conference on Software Engineering

May 2024

2942 pages

ISBN:9798400702174

DOI:10.1145/3597503

Co-chairs:
Ana Paiva,
Rui Abreu,
Program Co-chairs:
Abhik Roychoudhury,
Margaret Storey

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Published: 06 February 2024

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the National Key Research and Development Program of China
the National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province, China
CCF-Huawei Populus Grove Fund
NSF (National Science Foundation)

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ICSE '24: IEEE/ACM 46th International Conference on Software Engineering

April 14 - 20, 2024

Lisbon, Portugal

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Cited By

Huang KXu ZYang SSun HLi XYan ZZhang Y(2024)Evolving Paradigms in Automated Program Repair: Taxonomy, Challenges, and OpportunitiesACM Computing Surveys10.1145/369645057:2(1-43)Online publication date: 10-Oct-2024
https://dl.acm.org/doi/10.1145/3696450
Xin QWu HTang JLiu XReiss SXuan J(2024)Detecting, Creating, Repairing, and Understanding Indivisible Multi-Hunk BugsProceedings of the ACM on Software Engineering10.1145/36608281:FSE(2747-2770)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3660828

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