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Automatic inference of code transforms for patch generation

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Martin RinardAuthors Info & Claims

ESEC/FSE 2017: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

Pages 727 - 739

https://doi.org/10.1145/3106237.3106253

Published: 21 August 2017 Publication History

Abstract

We present a new system, Genesis, that processes human patches to automatically infer code transforms for automatic patch generation. We present results that characterize the effectiveness of the Genesis inference algorithms and the complete Genesis patch generation system working with real-world patches and defects collected from 372 Java projects. To the best of our knowledge, Genesis is the first system to automatically infer patch generation transforms or candidate patch search spaces from previous successful patches.

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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
Lin RFu YYi WYang JCao JDong ZXie FLi H(2024)Vulnerabilities and Security Patches Detection in OSS: A SurveyACM Computing Surveys10.1145/369478257:1(1-37)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3694782
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
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Index Terms

Automatic inference of code transforms for patch generation
1. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Automatic programming
    2. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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cover image ACM Conferences

ESEC/FSE 2017: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

August 2017

1073 pages

ISBN:9781450351058

DOI:10.1145/3106237

General Chairs:
Eric Bodden
Paderborn University, Germany / Fraunhofer IEM, Germany
,
Wilhelm Schäfer
Paderborn University, Germany
,
Program Chairs:
Arie van Deursen
Delft University of Technology, Netherlands
,
Andrea Zisman
Open University, UK

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Published: 21 August 2017

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ESEC/FSE'17: Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering

September 4 - 8, 2017

Paderborn, Germany

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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
Lin RFu YYi WYang JCao JDong ZXie FLi H(2024)Vulnerabilities and Security Patches Detection in OSS: A SurveyACM Computing Surveys10.1145/369478257:1(1-37)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3694782
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
Lee MBak JMoon SJhi YOh HFilkov VRay BZhou M(2024)Effective Unit Test Generation for Java Null Pointer ExceptionsProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695484(1044-1056)Online publication date: 27-Oct-2024
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Lou YYang JBenton SHao DTan LChen ZZhang LZhang L(2024)When Automated Program Repair Meets Regression Testing—An Extensive Study on Two Million PatchesACM Transactions on Software Engineering and Methodology10.1145/367245033:7(1-23)Online publication date: 13-Jun-2024
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Wang XYu HMeng XCao HZhang HSun HLiu XHu C(2024)MTL-TRANSFER: Leveraging Multi-task Learning and Transferred Knowledge for Improving Fault Localization and Program RepairACM Transactions on Software Engineering and Methodology10.1145/365444133:6(1-31)Online publication date: 27-Jun-2024
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