Article

Locating causes of program failures

Authors:

Andreas ZellerAuthors Info & Claims

ICSE '05: Proceedings of the 27th international conference on Software engineering

Pages 342 - 351

https://doi.org/10.1145/1062455.1062522

Published: 15 May 2005 Publication History

Abstract

Which is the defect that causes a software failure? By comparing the program states of a failing and a passing run, we can identify the state differences that cause the failure. However, these state differences can occur all over the program run. Therefore, we focus in space on those variables and values that are relevant for the failure, and in time on those moments where cause transitions occur---moments where new relevant variables begin being failure causes: "Initially, variable argc was 3; therefore, at shell_sort(), variable [2] was 0, and therefore, the program failed." In our evaluation, cause transitions locate the failure-inducing defect twice as well as the best methods known so far.

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Index Terms

Locating causes of program failures
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Process validation
        Traceability
      2. Software defect analysis
        Software testing and debugging

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Information

Published In

cover image ACM Conferences

ICSE '05: Proceedings of the 27th international conference on Software engineering

May 2005

754 pages

ISBN:1581139632

DOI:10.1145/1062455

General Chair:
Gruia-Catalin Roman
Washington University in St. Louis
,
Program Chairs:
William Griswold
University of California, San Diego
,
Bashar Nuseibeh
The Open University, UK

Copyright © 2005 ACM.

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Published: 15 May 2005

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ICSE05: 27th International Conference on Software Engineering

May 15 - 21, 2005

MO, St. Louis, USA

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Cited By

Chen JWang JSun YCheng PChen JChristakis MPradel M(2024)Isolation-Based Debugging for Neural NetworksProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652132(338-349)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3652132
Song XWu YLiu SChen BLin YPeng XChristakis MPradel M(2024)C2D2: Extracting Critical Changes for Real-World Bugs with Dependency-Sensitive Delta DebuggingProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652129(300-312)Online publication date: 11-Sep-2024
https://dl.acm.org/doi/10.1145/3650212.3652129
Jiang JYang JZhang YWang ZYou HChen J(2024)A Post-training Framework for Improving the Performance of Deep Learning Models via Model TransformationACM Transactions on Software Engineering and Methodology10.1145/363001133:3(1-41)Online publication date: 15-Mar-2024
https://dl.acm.org/doi/10.1145/3630011
Srivastava SDutta AMall R(2024)Effective fault localization using probabilistic and grouping approachInternational Journal of System Assurance Engineering and Management10.1007/s13198-024-02479-515:9(4616-4635)Online publication date: 18-Aug-2024
https://doi.org/10.1007/s13198-024-02479-5
Rezaalipour MFuria C(2024)An empirical study of fault localization in Python programsEmpirical Software Engineering10.1007/s10664-024-10475-329:4Online publication date: 13-Jun-2024
https://dl.acm.org/doi/10.1007/s10664-024-10475-3
Valnet MCourant NBury GChambart PLaviron V(2024)Chamelon : A Delta-Debugger for OCamlFormal Methods10.1007/978-3-031-71177-0_6(76-83)Online publication date: 13-Sep-2024
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Wu SLo J(2023)The MADAG Strategy for Fault Location TechniquesApplied Sciences10.3390/app1302081913:2(819)Online publication date: 6-Jan-2023
https://doi.org/10.3390/app13020819
Zuo ZNiu XZhang SFang LKhoo SLu SSun CXu G(2023)Toward More Efficient Statistical Debugging with Abstraction RefinementACM Transactions on Software Engineering and Methodology10.1145/354479032:2(1-38)Online publication date: 30-Mar-2023
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Etemadi KSharma AMadeiral FMonperrus M(2023)Augmenting Diffs With Runtime InformationIEEE Transactions on Software Engineering10.1109/TSE.2023.332425849:11(4988-5007)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1109/TSE.2023.3324258
Soremekun EKirschner LBöhme MPapadakis MGrundy JPollock LPenta M(2023)Evaluating the Impact of Experimental Assumptions in Automated Fault LocalizationProceedings of the 45th International Conference on Software Engineering10.1109/ICSE48619.2023.00025(159-171)Online publication date: 14-May-2023
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