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Software Fault Localization Using DStar (D*)

Published: 20 June 2012 Publication History

Abstract

Effective debugging is crucial to producing dependable software. Manual debugging is becoming prohibitively expensive, especially due to the growing size and complexity of programs. Given that fault localization is one of the most expensive activities in program debugging, there has been a great demand for fault localization techniques that can help guide programmers to the locations of faults. In this paper a technique named DStar (D*), which has its origins rooted in similarity coefficient-based analysis, is proposed, which can identify suspicious locations for fault localization automatically without requiring any prior information on program structure or semantics. D* is evaluated across 21 programs and is compared to 16 different fault localization techniques. Both single-fault and multi-fault programs are used. Results indicate that D* is more effective at locating faults than all the other techniques it is compared to.

Cited By

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  • (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
  • (2024)Traceback: A Fault Localization Technique for Molecular ProgramsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652138(415-427)Online publication date: 11-Sep-2024
  • (2024)Application Monitoring for bug reproduction in web-based applicationsJournal of Systems and Software10.1016/j.jss.2023.111834207:COnline publication date: 1-Jan-2024
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    cover image Guide Proceedings
    SERE '12: Proceedings of the 2012 IEEE Sixth International Conference on Software Security and Reliability
    June 2012
    302 pages
    ISBN:9780769547428

    Publisher

    IEEE Computer Society

    United States

    Publication History

    Published: 20 June 2012

    Author Tags

    1. Testing
    2. debugging
    3. software fault localization

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    View all
    • (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
    • (2024)Traceback: A Fault Localization Technique for Molecular ProgramsProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3652138(415-427)Online publication date: 11-Sep-2024
    • (2024)Application Monitoring for bug reproduction in web-based applicationsJournal of Systems and Software10.1016/j.jss.2023.111834207:COnline publication date: 1-Jan-2024
    • (2024)A systematic mapping study of bug reproduction and localizationInformation and Software Technology10.1016/j.infsof.2023.107338165:COnline publication date: 1-Jan-2024
    • (2024)Improving fault localization via weighted execution graph and graph attention networkJournal of Software: Evolution and Process10.1002/smr.261936:6Online publication date: 5-Jun-2024
    • (2023)SupConFL: Fault Localization with Supervised Contrastive LearningProceedings of the 14th Asia-Pacific Symposium on Internetware10.1145/3609437.3609441(44-54)Online publication date: 4-Aug-2023
    • (2023)Influential Global and Local Contexts Guided Trace Representation for Fault LocalizationACM Transactions on Software Engineering and Methodology10.1145/357604332:3(1-27)Online publication date: 26-Apr-2023
    • (2023)A fault localization approach based on fault propagation contextInformation and Software Technology10.1016/j.infsof.2023.107245160:COnline publication date: 1-Aug-2023
    • (2023)Spectrum‐based fault localization using empirical mode decomposition algorithmJournal of Software: Evolution and Process10.1002/smr.254636:4Online publication date: 27-Feb-2023
    • (2022)SFLKit: a workbench for statistical fault localizationProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558915(1701-1705)Online publication date: 7-Nov-2022
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