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.

References

[1]

J. Bowring, A. Orso, and M. J. Harrold. Monitoring deployed software using software tomography. In M. B. Dwyer, editor, Proceedings of the 2002 ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering (PASTE-02), volume 28, 1 of SOFTWARE ENGINEERING NOTES, pages 2--9. ACM Press, 2002.

Digital Library

[2]

L. Burnell and E. Horvitz. Structure and chance: melding logic and probability for software debugging. Communications of the ACM, 38(3):31--41, 57, Mar. 1995.

Digital Library

[3]

T. Chilimbi and M. Hauswirth. Low-overhead memory leak detection using adaptive statistical profiling. In ASPLOS: Eleventh International Conference on Architectural Support for Programming Languages and Operating Systems, Boston, MA, Oct. 2004.

Digital Library

[4]

S. Elbaum and M. Hardojo. Deploying instrumented software to assist the testing activity. In RAMSS 2003 RAMSS:2003, pages 31--33.

[5]

M. D. Ernst, J. Cockrell, W. G. Griswold, and D. Notkin. Dynamically discovering likely program invariants to support program evolution. IEEE Transactions on Software Engineering, 27(2):1--25, Feb. 2001.

Digital Library

[6]

K. C. Gross, S. McMaster, A. Porter, A. Urmanov, and L. G. Votta. Proactive system maintenance using software telemetry. In RAMSS 2003 RAMSS:2003, pages 24--26.

[7]

S. Hangal and M. S. Lam. Tracking down software bugs using automatic anomaly detection. In Proceedings of the 24th International Conference on Software Engineering (ICSE-02), pages 291--301. ACM Press, 2002.

Digital Library

[8]

E. Lehmann. Testing Statistical Hypotheses. John Wiley & Sons, 2nd edition, 1986.

[9]

E. Lehmann and G. Casella. Theory of Point Estimation. Springer, 2nd edition, 2003.

[10]

B. Liblit, A. Aiken, A. X. Zheng, and M. I. Jordan. Bug isolation via remote program sampling. In J. James B. Fenwick and C. Norris, editors, Proceedings of the ACM SIGPLAN 2003 Conference on Programming Language Design and Implementation (PLDI-03), volume 38, 5 of ACM SIGPLAN Notices, pages 141--154. ACM Press, 2003.

Digital Library

[11]

B. Liblit, M. Naik, A. X. Zheng, A. Aiken, and M. I. Jordan. Public deployment of cooperative bug isolation. In Proceedings of the Second International Workshop on Remote Analysis and Measurement of Software Systems (RAMSS '04), pages 57--62, Edinburgh, Scotland, May 24 2004.

[12]

A. Orso, T. Apiwattanapong, and M. J. Harrold. Leveraging field data for impact analysis and regression testing. In Proceedings of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering, pages 128--137. ACM Press, 2003.

Digital Library

[13]

A. Podgurski, D. Leon, P. Francis, W. Masri, M. Minch, J. Sun, and B. Wang. Automated support for classifying software failure reports. In Proceedings of the 25th International Conference on Software Engineering (ICSE-03), pages 465--477. IEEE Computer Society, 2003.

Digital Library

[14]

RAMSS '03: The 1st International Workshop on Remote Analysis and Measurement of Software Systems, May 2003.

Digital Library

[15]

S. Schleimer, D. S. Wilkerson, and A. Aiken. Winnowing: local algorithms for document fingerprinting. In ACM, editor, Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data 2003, San Diego, California, June 09--12, 2003, pages 76--85, New York, NY 10036, USA, 2003. ACM Press.

Digital Library

[16]

A. X. Zheng, M. I. Jordan, B. Liblit, and A. Aiken. Statistical debugging of sampled programs. In S. Thrun, L. Saul, and B. Schölkopf, editors, Advances in Neural Information Processing Systems 16. MIT Press, Cambridge, MA, 2004.

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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
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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
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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.

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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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

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
Park YLee HJung JKoo HKim H(2024)Benzene: A Practical Root Cause Analysis System with an Under-Constrained State Mutation2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00074(1865-1883)Online publication date: 19-May-2024
https://doi.org/10.1109/SP54263.2024.00074
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
https://doi.org/10.1109/ICST60714.2024.00014
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
https://doi.org/10.1109/ICST60714.2024.00013
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
https://doi.org/10.1007/s11432-022-3803-9
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
https://doi.org/10.1007/s11334-024-00558-1
Zhan GCheng SZhang J(2024)Mutate Suspicious Statements to Locate FaultsIntelligence Computation and Applications10.1007/978-981-97-4396-4_38(407-418)Online publication date: 1-Jul-2024
https://doi.org/10.1007/978-981-97-4396-4_38
Jiang JWang YChen JLv DLiu M(2023)Variable-Based Fault Localization via Enhanced Decision TreeACM Transactions on Software Engineering and Methodology10.1145/3624741Online publication date: 18-Sep-2023
https://dl.acm.org/doi/10.1145/3624741
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