Article

A topic-based approach for narrowing the search space of buggy files from a bug report

Authors:

Anh Tuan Nguyen,

Tung Thanh Nguyen,

Jafar Al-Kofahi,

Hung Viet Nguyen,

Tien N. NguyenAuthors Info & Claims

ASE '11: Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering

Pages 263 - 272

https://doi.org/10.1109/ASE.2011.6100062

Published: 06 November 2011 Publication History

Abstract

Locating buggy code is a time-consuming task in software development. Given a new bug report, developers must search through a large number of files in a project to locate buggy code. We propose BugScout, an automated approach to help developers reduce such efforts by narrowing the search space of buggy files when they are assigned to address a bug report. BugScout assumes that the textual contents of a bug report and that of its corresponding source code share some technical aspects of the system which can be used for locating buggy source files given a new bug report. We develop a specialized topic model that represents those technical aspects as topics in the textual contents of bug reports and source files, and correlates bug reports and corresponding buggy files via their shared topics. Our evaluation shows that BugScout can recommend buggy files correctly up to 45% of the cases with a recommended ranked list of 10 files.

References

[1]

H. U. Asuncion, A. U. Asuncion, and R. N. Taylor. Software traceability with topic modeling. In ICSE '10, pages 95-104. ACM Press, 2010.

Digital Library

[2]

A. Bacchelli, M. Lanza, and R. Robbes. Linking e-mails and source code artifacts. In ICSE '10, pages 375-384. ACM Press, 2010.

Digital Library

[3]

R. M. Bell, T. J. Ostrand, and E. J. Weyuker. Looking for bugs in all the right places. In ISSTA '06, pages 61-72. ACM Press, 2006.

Digital Library

[4]

D. Blei, A.Y. Ng, and M. Jordan. Latent Dirichlet Allocation. J. Mach. Learn. Res. 3 (Mar. 2003), 993-1022.

Digital Library

[5]

C. Chang and C. Lin, LIBSVM: library for support vector machines.

[6]

G. Canfora and L. Cerulo. How software repositories can help in resolving a new change request. In Workshop on Empirical Studies in Reverse Engineering, 2005.

[7]

T. Griffiths, Gibbs sampling in the generative model of Latent Dirichlet Allocation. Technical Report, 2002.

[8]

A. E. Hassan. Predicting faults using the complexity of code changes. In ICSE '09, pages 78-88. IEEE CS, 2009.

Digital Library

[9]

S. Kim, T. Zimmermann, J. Whitehead, Jr., and A. Zeller. Predicting faults from cached history. In ICSE'07, pages 489-498. IEEE CS, 2007.

Digital Library

[10]

E. Linstead, P. Rigor, S. Bajracharya, C. Lopes, and P. Baldi. Mining concepts from code with probabilistic topic models. In ASE'07, ACM.

Digital Library

[11]

D. Liu, A. Marcus, D. Poshyvanyk, and V. Rajlich. Feature location via information retrieval based filtering of a single scenario execution trace. In ASE '07, pp. 234-243. ACM Press, 2007.

Digital Library

[12]

S. K. Lukins, N. A. Kraft, and L. H. Etzkorn. Bug localization using latent dirichlet allocation. J. of Inf. Softw. Technol., 52(9):972-990, 2010.

Digital Library

[13]

A. Marcus and J. I. Maletic. Recovering documentation to source code traceability links using Latent Semantic Indexing. In ICSE'03, IEEE.

Digital Library

[14]

T. Menzies, J. Greenwald, and A. Frank. Data mining static code attributes to learn defect predictors. IEEE TSE, 33(1):2-13, 2007.

Digital Library

[15]

R. Moser, W. Pedrycz, and G. Succi. A comparative analysis of the efficiency of change metrics and static code attributes for defect prediction. In ICSE '08, pages 181-190. ACM Press, 2008.

Digital Library

[16]

N. Nagappan, T. Ball, and A. Zeller. Mining metrics to predict component failures. In ICSE '06, pages 452-461. ACM Press, 2006.

Digital Library

[17]

N. Nagappan, A. Zeller, T. Zimmermann, K. Herzig, and B. Murphy. Change bursts as defect predictors. In ISSRE'10, pp. 309-318. IEEE CS.

Digital Library

[18]

T. J. Ostrand, E. J. Weyuker, R. Bell. Predicting the location and number of faults in large software systems. IEEE TSE, 31(4):340-355, 2005.

Digital Library

[19]

R. Premraj, I.-X. Chen, H. Jaygarl, T.N. Nguyen, T. Zimmermann, S. Kim, and A. Zeller. Where should I fix this bug? (bugtalks.wikispaces.com), 2008.

[20]

A. E. Raftery and S. Lewis. How Many Iterations in the Gibbs Sampler. In Bayesian Statistics 4. Oxford University Press, pp. 763-773, 1992.

[21]

J. Ratzinger, M. Pinzger, and H. Gall. EQ-mine: Predicting short-term defects for software evolution. In FASE'07, pp. 12-26. Springer-Verlag.

Digital Library

[22]

J. Sliwerski, T. Zimmermann, and A. Zeller. Hatari: raising risk awareness. In ESEC/FSE-13, pages 107-110. ACM Press, 2005.

Digital Library

[23]

T. Zimmermann and N. Nagappan. Predicting defects using network analysis on dependency graphs. In ICSE'08, pp. 531-540. ACM, 2008.

Digital Library

[24]

V. Dallmeier and T. Zimmermann. Extraction of bug localization benchmarks from history. In ASE'07, pages 433-436. ACM Press, 2007.

Digital Library

Cited By

Yoon DWang YYu MHuang EJones JKukkadapu AKocas OWiepert JGoenka KChen SLin YHuang ZKong JChow MTang CWitchel EArpaci-Dusseau ARossbach CKeeton K(2024)FBDetect: Catching Tiny Performance Regressions at Hyperscale through In-Production MonitoringProceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles10.1145/3694715.3695977(522-540)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3694715.3695977
Zhang LRoychoudhury APaiva AAbreu RStorey M(2024)Vulnerability Root Cause Function Locating For Java VulnerabilitiesProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3641225(444-446)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3639478.3641225
Qi BSun HZhang HGao X(2024)Reusing Convolutional Neural Network Models through Modularization and CompositionACM Transactions on Software Engineering and Methodology10.1145/363274433:3(1-39)Online publication date: 15-Mar-2024
https://dl.acm.org/doi/10.1145/3632744
Show More Cited By

Recommendations

Faceted Bug Report Search with Topic Model
COMPSAC '14: Proceedings of the 2014 IEEE 38th Annual Computer Software and Applications Conference

During bug reporting, The same bugs could be repeatedly reported. As a result, extra time could be spent on bug triaging and fixing. In order to reduce redundant effort, it is important to provide bug reporters with the ability to search for previously ...
Towards Semi-automatic Bug Triage and Severity Prediction Based on Topic Model and Multi-feature of Bug Reports
COMPSAC '14: Proceedings of the 2014 IEEE 38th Annual Computer Software and Applications Conference

Bug fixing is an essential activity in the software maintenance, because most of the software systems have unavoidable defects. When new bugs are submitted, triagers have to find and assign appropriate developers to fix the bugs. However, if the bugs are ...
Detecting Buggy Files based on Bug Reports: A Random Walk Based Approach
Internetware '15: Proceedings of the 7th Asia-Pacific Symposium on Internetware

During an Open Source Software (OSS) maintenance, bug localization is a laborsome and time-consuming work for geographically-separated developers. It is desirable to automatically identify related buggy files once a bug report is submitted. Existing ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ASE '11: Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering

November 2011

677 pages

ISBN:9781457716386

Sponsors

Publisher

IEEE Computer Society

United States

Publication History

Published: 06 November 2011

Check for updates

Qualifiers

Article

Conference

ASE '11

Sponsor:

ASE '11: Automated Software Engineering

November 6 - 10, 2011

Acceptance Rates

Overall Acceptance Rate 82 of 337 submissions, 24%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

55
Total Citations
View Citations
245
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)2

Reflects downloads up to 25 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Yoon DWang YYu MHuang EJones JKukkadapu AKocas OWiepert JGoenka KChen SLin YHuang ZKong JChow MTang CWitchel EArpaci-Dusseau ARossbach CKeeton K(2024)FBDetect: Catching Tiny Performance Regressions at Hyperscale through In-Production MonitoringProceedings of the ACM SIGOPS 30th Symposium on Operating Systems Principles10.1145/3694715.3695977(522-540)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3694715.3695977
Zhang LRoychoudhury APaiva AAbreu RStorey M(2024)Vulnerability Root Cause Function Locating For Java VulnerabilitiesProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3641225(444-446)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3639478.3641225
Qi BSun HZhang HGao X(2024)Reusing Convolutional Neural Network Models through Modularization and CompositionACM Transactions on Software Engineering and Methodology10.1145/363274433:3(1-39)Online publication date: 15-Mar-2024
https://dl.acm.org/doi/10.1145/3632744
Aljedaani WMkaouer MEler MKessentini M(2024)Empirical Investigation of Accessibility Bug Reports in Mobile Platforms: A Chromium Case StudyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642508(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642508
Kim KGhatpande SKim DZhou XLiu KBissyandé TKlein JLe Traon Y(2023)Big Code Search: A BibliographyACM Computing Surveys10.1145/360490556:1(1-49)Online publication date: 26-Aug-2023
https://dl.acm.org/doi/10.1145/3604905
Oliveira ADos Santos PMarcílio Júnior WAljedaani WEler DEler M(2023)Analyzing Accessibility Reviews Associated with Visual Disabilities or Eye ConditionsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581315(1-14)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581315
Li HYan MSun WLiu XWu Y(2023)A first look at bug report templates on GitHubJournal of Systems and Software10.1016/j.jss.2023.111709202:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111709
Hamdy AArabi A(2022)Locating Faulty Source Code Files to Fix Bug ReportsInternational Journal of Open Source Software and Processes10.4018/IJOSSP.30879113:1(1-15)Online publication date: 16-Sep-2022
https://dl.acm.org/doi/10.4018/IJOSSP.308791
Ciborowska ADamevski KDwyer MDamian DZeller A(2022)Fast changeset-based bug localization with BERTProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510042(946-957)Online publication date: 21-May-2022
https://dl.acm.org/doi/10.1145/3510003.3510042
Yang YXia XLo DBi TGrundy JYang X(2022)Predictive Models in Software Engineering: Challenges and OpportunitiesACM Transactions on Software Engineering and Methodology10.1145/350350931:3(1-72)Online publication date: 9-Apr-2022
https://dl.acm.org/doi/10.1145/3503509
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents