Article

Duplicate bug report detection with a combination of information retrieval and topic modeling

Authors:

Anh Tuan Nguyen,

Tung Thanh Nguyen,

Tien N. Nguyen,

Chengnian SunAuthors Info & Claims

ASE '12: Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering

September 2012

Pages 70 - 79

https://doi.org/10.1145/2351676.2351687

Published: 03 September 2012 Publication History

Abstract

Detecting duplicate bug reports helps reduce triaging efforts and save time for developers in fixing the same issues. Among several automated detection approaches, text-based information retrieval (IR) approaches have been shown to outperform others in term of both accuracy and time efficiency. However, those IR-based approaches do not detect well the duplicate reports on the same technical issues written in different descriptive terms.

This paper introduces DBTM, a duplicate bug report detection approach that takes advantage of both IR-based features and topic-based features. DBTM models a bug report as a textual document describing certain technical issue(s), and models duplicate bug reports as the ones about the same technical issue(s). Trained with historical data including identified duplicate reports, it is able to learn the sets of different terms describing the same technical issues and to detect other not-yet-identified duplicate ones. Our empirical evaluation on real-world systems shows that DBTM improves the state-of-the-art approaches by up to 20% in accuracy.

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Cited By

Yu SFang CZhang QDu MLiu JChen Z(2024)Semi-supervised Crowdsourced Test Report Clustering via Screenshot-Text Binding RulesProceedings of the ACM on Software Engineering10.1145/36607761:FSE(1540-1563)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3660776
Speth SRoychoudhury APaiva AAbreu RStorey M(2024)Architecture-Based Cross-Component Issue Management and Propagation AnalysisProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3639814(145-149)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3639478.3639814
Yan YCooper NChaparro OMoran KPoshyvanyk DRoychoudhury APaiva AAbreu RStorey M(2024)Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug ReportsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639163(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639163
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Index Terms

Duplicate bug report detection with a combination of information retrieval and topic modeling
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Software management
        Software maintenance
2. Software and its engineering
  1. Software creation and management
    1. Software post-development issues

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cover image ACM Conferences

ASE '12: Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering

September 2012

409 pages

ISBN:9781450312042

DOI:10.1145/2351676

General Chair:
Michael Goedicke,
Program Chairs:
Tim Menzies,
Motoshi Saeki

Copyright © 2012 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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Universität Duisburg Essen: Universität Duisburg Essen
TCSE: IEEE Computer Society's Tech. Council on Software Engin.

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Association for Computing Machinery

New York, NY, United States

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Published: 03 September 2012

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ASE'12: IEEE/ACM International Conference on Automated Software Engineering

September 3 - 7, 2012

Essen, Germany

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Cited By

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https://dl.acm.org/doi/10.1145/3660776
Speth SRoychoudhury APaiva AAbreu RStorey M(2024)Architecture-Based Cross-Component Issue Management and Propagation AnalysisProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3639814(145-149)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3639478.3639814
Yan YCooper NChaparro OMoran KPoshyvanyk DRoychoudhury APaiva AAbreu RStorey M(2024)Semantic GUI Scene Learning and Video Alignment for Detecting Duplicate Video-based Bug ReportsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639163(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639163
Zuo FRhee J(2024)Vulnerability discovery based on source code patch commit mining: a systematic literature reviewInternational Journal of Information Security10.1007/s10207-023-00795-823:2(1513-1526)Online publication date: 6-Jan-2024
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Elmarkez AMesli-Kesraoui SOquendo FBerruet PKesraoui D(2024)A Similarity Approach for the Classification of Mitigations in Public Cybersecurity Repositories into NIST-SP 800-53 CatalogInformation Security Theory and Practice10.1007/978-3-031-60391-4_5(64-79)Online publication date: 18-Jun-2024
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Fazzini MMoran KBernal-Cardenas CWendland TOrso APoshyvanyk D(2023)Enhancing Mobile App Bug Reporting via Real-Time Understanding of Reproduction StepsIEEE Transactions on Software Engineering10.1109/TSE.2022.317402849:3(1246-1272)Online publication date: 1-Mar-2023
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