article

Scalable statistical bug isolation

Authors:

Alice X. Zheng,

Michael I. JordanAuthors Info & Claims

ACM SIGPLAN Notices, Volume 40, Issue 6

Pages 15 - 26

https://doi.org/10.1145/1064978.1065014

Published: 12 June 2005 Publication History

Abstract

We present a statistical debugging algorithm that isolates bugs in programs containing multiple undiagnosed bugs. Earlier statistical algorithms that focus solely on identifying predictors that correlate with program failure perform poorly when there are multiple bugs. Our new technique separates the effects of different bugs and identifies predictors that are associated with individual bugs. These predictors reveal both the circumstances under which bugs occur as well as the frequencies of failure modes, making it easier to prioritize debugging efforts. Our algorithm is validated using several case studies, including examples in which the algorithm identified previously unknown, significant crashing bugs in widely used systems.

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Information & Contributors

Information

Published In

cover image ACM SIGPLAN Notices

ACM SIGPLAN Notices Volume 40, Issue 6

Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation

June 2005

325 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/1064978

Issue’s Table of Contents

PLDI '05: Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
June 2005
338 pages
ISBN:1595930566
DOI:10.1145/1065010
General Chair:
Vivek Sarkar
IBM Research
,
Program Chair:
Mary Hall
USC/ISI

Copyright © 2005 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2005

Published in SIGPLAN Volume 40, Issue 6

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Cited By

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https://dl.acm.org/doi/10.5555/3698900.3699137
Sruthi PGuo ZChu DChen ZZhang Y(2024)Demystifying the Fight Against Complexity: A Comprehensive Study of Live Debugging Activities in Production Cloud SystemsProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698568(341-360)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3698038.3698568
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
https://dl.acm.org/doi/10.1145/3654441
Fu YWang TLi SDing JZhou SJia ZLi WJiang YLiao XRoychoudhury APaiva AAbreu RStorey M(2024)MissConf: LLM-Enhanced Reproduction of Configuration-Triggered BugsProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3647635(484-495)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3639478.3647635
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Yan ZHaipeng QYing LLiu KChao Q(2024)Enhanced Fast and Reliable Statistical Vulnerability Root Cause Analysis with Sanitizer2024 IEEE Conference on Software Testing, Verification and Validation (ICST)10.1109/ICST60714.2024.00014(47-58)Online publication date: 27-May-2024
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Zhang YWang YZhu DLiu W(2024)FusionFL: A Statement-Level Feature Fusion Based Fault Localization Approach2024 IEEE Conference on Software Testing, Verification and Validation (ICST)10.1109/ICST60714.2024.00013(37-46)Online publication date: 27-May-2024
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Chen XHu XHuang YJiang HJi WJiang YJiang YLiu BLiu HLi XLian XMeng GPeng XSun HShi LWang BWang CWang JWang TXuan JXia XYang YYang YZhang LZhou YZhang L(2024)Deep learning-based software engineering: progress, challenges, and opportunitiesScience China Information Sciences10.1007/s11432-023-4127-568:1Online publication date: 24-Dec-2024
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Song YXie XXu B(2024)When debugging encounters artificial intelligence: state of the art and open challengesScience China Information Sciences10.1007/s11432-022-3803-967:4Online publication date: 21-Feb-2024
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Bekkouche M(2024)A bounded constraint-based approach to aid in fault localization from a counterexampleInnovations in Systems and Software Engineering10.1007/s11334-024-00558-1Online publication date: 12-Apr-2024
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