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Beyond Tests: Program Vulnerability Repair via Crash Constraint Extraction

Authors:

Gregory J. Duck,

Abhik RoychoudhuryAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology (TOSEM), Volume 30, Issue 2

Article No.: 14, Pages 1 - 27

https://doi.org/10.1145/3418461

Published: 10 February 2021 Publication History

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Abstract

Automated program repair is an emerging technology that seeks to automatically rectify program errors and vulnerabilities. Repair techniques are driven by a correctness criterion that is often in the form of a test suite. Such test-based repair may produce overfitting patches, where the patches produced fail on tests outside the test suite driving the repair. In this work, we present a repair method that fixes program vulnerabilities without the need for a voluminous test suite. Given a vulnerability as evidenced by an exploit, the technique extracts a constraint representing the vulnerability with the help of sanitizers. The extracted constraint serves as a proof obligation that our synthesized patch should satisfy. The proof obligation is met by propagating the extracted constraint to locations that are deemed to be “suitable” fix locations. An implementation of our approach (ExtractFix) on top of the KLEE symbolic execution engine shows its efficacy in fixing a wide range of vulnerabilities taken from the ManyBugs benchmark, real-world CVEs and Google’s OSS-Fuzz framework. We believe that our work presents a way forward for the overfitting problem in program repair by generalizing observable hazards/vulnerabilities (as constraint) from a single failing test or exploit.

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Cited By

Cao HHan DChu YTian FWang YLiu YJia JGe H(2024)Multi-mechanism neural machine translation framework for automatic program repairJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23403746:4(7859-7873)Online publication date: 18-Apr-2024
https://doi.org/10.3233/JIFS-234037
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
Tufano RMastropaolo APepe FDabic ODi Penta MBavota GSpinellis DConstantinou EBacchelli A(2024)Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based StudyProceedings of the 21st International Conference on Mining Software Repositories10.1145/3643991.3644918(571-583)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3643991.3644918
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Index Terms

Beyond Tests: Program Vulnerability Repair via Crash Constraint Extraction
1. Security and privacy
  1. Software and application security
    1. Software security engineering
2. 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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Published In

cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 30, Issue 2

Continuous Special Section: AI and SE

April 2021

463 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/3446657

Editor:
Mauro Pezzè
Università della Svizzera italiana and Università di Milano-Bicocca, Switzerland

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Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 February 2021

Accepted: 01 August 2020

Revised: 01 June 2020

Received: 01 December 2019

Published in TOSEM Volume 30, Issue 2

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National Research Foundation (NRF) Singapore
National Cybersecurity R8D (NCR) programme
National Satellite of Excellence in Trustworthy Software Systems
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province

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Cited By

Cao HHan DChu YTian FWang YLiu YJia JGe H(2024)Multi-mechanism neural machine translation framework for automatic program repairJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23403746:4(7859-7873)Online publication date: 18-Apr-2024
https://doi.org/10.3233/JIFS-234037
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
Tufano RMastropaolo APepe FDabic ODi Penta MBavota GSpinellis DConstantinou EBacchelli A(2024)Unveiling ChatGPT's Usage in Open Source Projects: A Mining-based StudyProceedings of the 21st International Conference on Mining Software Repositories10.1145/3643991.3644918(571-583)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3643991.3644918
Zhou XKim KXu BHan DLo DRoychoudhury APaiva AAbreu RStorey M(2024)Out of Sight, Out of Mind: Better Automatic Vulnerability Repair by Broadening Input Ranges and SourcesProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639222(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639222
Huang ZWang CRoychoudhury APaiva AAbreu RStorey M(2024)Constraint Based Program Repair for Persistent Memory BugsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639204(1-12)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639204
Zhang QFang CYu BSun WZhang TChen Z(2024)Pre-Trained Model-Based Automated Software Vulnerability Repair: How Far are We?IEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2023.330889721:4(2507-2525)Online publication date: Jul-2024
https://doi.org/10.1109/TDSC.2023.3308897
Liu PWang HZheng CZhang Y(2024)Prompt Fix: Vulnerability Automatic Repair Technology Based on Prompt Engineering2024 International Conference on Computing, Networking and Communications (ICNC)10.1109/ICNC59896.2024.10556123(116-120)Online publication date: 19-Feb-2024
https://doi.org/10.1109/ICNC59896.2024.10556123
Papotti AParamitha RMassacci F(2024)On the acceptance by code reviewers of candidate security patches suggested by Automated Program Repair toolsEmpirical Software Engineering10.1007/s10664-024-10506-z29:5Online publication date: 3-Aug-2024
https://doi.org/10.1007/s10664-024-10506-z
Wang BLiu GLin YRen SLi HZhang D(2024)Enhanced evolutionary automated program repair by finer‐granularity ingredients and better search algorithmsJournal of Software: Evolution and Process10.1002/smr.262436:6Online publication date: 5-Jun-2024
https://dl.acm.org/doi/10.1002/smr.2624
Zhang QFang CMa YSun WChen Z(2023)A Survey of Learning-based Automated Program RepairACM Transactions on Software Engineering and Methodology10.1145/363197433:2(1-69)Online publication date: 23-Dec-2023
https://dl.acm.org/doi/10.1145/3631974
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