research-article

Utilizing a multi-developer network-based developer recommendation algorithm to fix bugs effectively

Authors:

Byungjeong LeeAuthors Info & Claims

SAC '14: Proceedings of the 29th Annual ACM Symposium on Applied Computing

Pages 1134 - 1139

https://doi.org/10.1145/2554850.2555008

Published: 24 March 2014 Publication History

Abstract

Recently, bug fixing has become an important part of software maintenance. In large-scale projects, developers rely on bug reports to guide any bug-fixing activities. Due to a great number of bug reports submitted into the bug repository, the workload of the triagers who are responsible for arranging developers to fix the given bugs is very high. In order to reduce the triagers' workload, a number of approaches (e.g., machine learning algorithms and social network metrics) were proposed to study who should fix the bug report. In this study, we propose a novel algorithm for developer recommendation. We first introduce a component and a similar bug-based selection process to verify the candidate fixers, then by adopting the number of comments and commits, we construct a multi-developer network so that ranking these candidates for finding the most appropriate fixer to resolve the given bug. In order to evaluate our work, we measured the effectiveness of our approach based on 3,008 bug reports from the JBoss Issue bug repository. We also compared the proposed approach to three previous studies. The result shows that our approach performs the task of bug triage effectively.

References

[1]

Xuan, J., Jiang, H., Ren, Z., Yan, J. and Luo, Z. Automatic Bug Triage Using Semi-Supervised Text Classification. In Proceedings of International Conference on Software Engineering and Knowledge Engineering. Knowledge System Institute Graduate School, 2010, pp. 209--214.

[2]

Jeong, G., Kim, S. and Zimmermann, T. Improving Bug Triage with Bug Tossing Graph. In Proceedings of Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering. ACM Press, 2009, pp. 111--120.

Digital Library

[3]

Anvik, J., Hiew, L. and Murphy, G. C. Who Should Fix This Bug? In Proceedings of International Conference on Software Engineering. IEEE CS Press, 2006, pp. 361--370.

Digital Library

[4]

Xuan, J., Jiang, H., Ren, Z. and Zou, W. Developer Prioritization in Bug Repositories. In Proceedings of International Conference on Software Engineering. IEEE Press, 2012, pp. 25--35.

Digital Library

[5]

Wu, W., Zhang, W., Yang, Y. and Wang, Q. DREX: Developer Recommendation with K-Nearest-Neighbor Search and Expertise Ranking. In Proceedings of Asia-Pacific Software Engineering Conference, 2011, pp. 389--396.

Digital Library

[6]

Matter, D., Kuhn, A. and Nierstrasz, O. Assigning Bug Reports Using a Vocabulary-Based Experience model of Developers. In Proceedings of International Working Conference on Mining Software Repositories, IEEE Press, 2009, pp. 131--140.

Digital Library

[7]

Zhang, T. and Lee, B. A Hybrid Bug Triage Algorithm for Developer Recommendation. In proceedings of ACM Symposium on Applied Computing, ACM Press, 2013, pp. 1088--1094.

Digital Library

[8]

Rao, S. and Kak, A. Retrieval from Software Libraries for Bug Localization: A Comparative Study of Generic and Composite Text Models. In Proceedings of International Working Conference on Mining Software Repositories, ACM Press, 2011, pp. 43--51.

Digital Library

[9]

Zhang, T. and Lee, B. An Automated Bug Triage Approach: A Concept Profile and Social Network Based Developer Recommendation. In Proceedings of International Conference on Intelligent Computing(LNCS 7389), Springer, 2012, pp. 505--512.

[10]

Cubranic, D. and Murphy, G. C. Automatic Bug Triage Using Text Classification. In Proceedings of International Conference on Software Engineering and Knowledge Engineering, Knowledge System Institute Graduate School, 2004, pp. 92--97.

[11]

Park, J., Lee, M., Kim, J., Hwang, S. and Kim, S. Cos-TRIAGE: A Cost-Aware Triage Algorithm for Bug Reporting System. In Proceedings of International Conference on Artificial Intelligence, 2011, pp. 264--273.

[12]

Ektefa, M., Sidi, F., Ibrahim, H., Jabar, M. A. and Memar, S. A Comparative Study in Classification Techniques for Unsupervised Record Linkage Model. Journal of Computer Science, Vol. 7(3), 2011, pp. 341--347.

[13]

Chen, I. X, Yang, C. Z, Lu, T. K. and Jaygarl, H. Implicit Social Network Model for Predicting and Tracking the Location of Faults. In Proceedings of IEEE International Computer Software and Applications Conference, IEEE CS press, 2008, pp. 136--143.

Digital Library

[14]

Ohira, M., Hassan, A. and Osawa, N. The Impact of Bug Management Patterns on Bug Fixing: A Case Study of Eclipse Projects. In Proceedings of IEEE International Conference on Software Maintenance, 2012, pp. 264--273.

Digital Library

[15]

Davis, J. and Goadrich, M. The Relationship between Precision-Recall and ROC Curves. In Proceedings of International Conference on Machine Learning, 2006, pp. 233--240.

Digital Library

[16]

Wu, R., Zhang, H., Kim, S. and Cheung, S. C. Relink: Recovering Links between Bugs and Changes. In Proceeding of Joint Meeting of the European Software Engineering Conference and ACM SIGSOFT Symposium on the Foundations of Software Engineering, ACM Press, 2011, pp. 15--25.

Digital Library

[17]

Wilcoxon, F. Individual comparisons by ranking methods. Biometrics Bulletin, Vol. 1, No. 6, 1945, pp. 80--83.

[18]

R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, 2012.

Cited By

Gupta CInácio PFreire M(2022)Improving software maintenance with improved bug triagingJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2021.10.01134:10(8757-8764)Online publication date: Nov-2022
https://doi.org/10.1016/j.jksuci.2021.10.011
Yadav ASingh S(2022)Automated Time Based Multi-Criteria Bug Triage Approach: Developer Working Efficiency and Social Network Based Developer Recommendation基于时间的自动化多标准缺陷分类方法:开发人员工作效率和基于社交网络的开发人员推荐Journal of Shanghai Jiaotong University (Science)10.1007/s12204-022-2448-z29:3(566-578)Online publication date: 28-May-2022
https://doi.org/10.1007/s12204-022-2448-z
Goyal ASardana N(2021)Analytical Study on Bug Triaging PracticesResearch Anthology on Recent Trends, Tools, and Implications of Computer Programming10.4018/978-1-7998-3016-0.ch049(1068-1094)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-3016-0.ch049
Show More Cited By

Index Terms

Utilizing a multi-developer network-based developer recommendation algorithm to fix bugs effectively
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

Recommendations

A hybrid bug triage algorithm for developer recommendation
SAC '13: Proceedings of the 28th Annual ACM Symposium on Applied Computing

With a great number of software applications that have been developed, software maintenance has become an important and challenging task, particularly due to the increasing scale of software projects. Even if developers can create and update bug reports ...
Effective Bug Triage Based on Historical Bug-Fix Information
ISSRE '14: Proceedings of the 2014 IEEE 25th International Symposium on Software Reliability Engineering

For complex and popular software, project teams could receive a large number of bug reports. It is often tedious and costly to manually assign these bug reports to developers who have the expertise to fix the bugs. Many bug triage techniques have been ...
An Integrated Approach using Developer Profiles with Temporal Dynamics for Assignee Recommendation in Non-Reproducible Bugs
Abstract
A vital component of the software framework is bug reports. Bug tracking systems are employed for handling and closing the reported bugs. Unfxed bugs hinder software reliability and also camoufage other bugs. Non-Reproducible bugs deteriorate the ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SAC '14: Proceedings of the 29th Annual ACM Symposium on Applied Computing

March 2014

1890 pages

ISBN:9781450324694

DOI:10.1145/2554850

Conference Chairs:
Yookun Cho
Seoul National University, Korea
,
Sung Y. Shin
South Dakota State University
,
Program Chairs:
Sangwook Kim
Kyungpook National University, Korea
,
Chih-Cheng Hung
Southern Polytechnic State University
,
Jiman Hong
Soongsil University, South Korea

Copyright © 2014 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]

Sponsors

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 March 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Seoul Metropolitan Government
Ministry of Education, Science and Technology

Conference

SAC 2014

Sponsor:

SIGAPP

SAC 2014: Symposium on Applied Computing

March 24 - 28, 2014

Gyeongju, Republic of Korea

Acceptance Rates

SAC '14 Paper Acceptance Rate 218 of 939 submissions, 23%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

Upcoming Conference

SAC '25

Sponsor:
sigapp

The 40th ACM/SIGAPP Symposium on Applied Computing

March 31 - April 4, 2025

Catania , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
236
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Gupta CInácio PFreire M(2022)Improving software maintenance with improved bug triagingJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2021.10.01134:10(8757-8764)Online publication date: Nov-2022
https://doi.org/10.1016/j.jksuci.2021.10.011
Yadav ASingh S(2022)Automated Time Based Multi-Criteria Bug Triage Approach: Developer Working Efficiency and Social Network Based Developer Recommendation基于时间的自动化多标准缺陷分类方法:开发人员工作效率和基于社交网络的开发人员推荐Journal of Shanghai Jiaotong University (Science)10.1007/s12204-022-2448-z29:3(566-578)Online publication date: 28-May-2022
https://doi.org/10.1007/s12204-022-2448-z
Goyal ASardana N(2021)Analytical Study on Bug Triaging PracticesResearch Anthology on Recent Trends, Tools, and Implications of Computer Programming10.4018/978-1-7998-3016-0.ch049(1068-1094)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-3016-0.ch049
Mahdi MMohamed Zabil MAhmad AIsmail RYusoff YCheng LAzmi MNatiq HHappala Naidu H(2021)Software Project Management Using Machine Learning Technique—A ReviewApplied Sciences10.3390/app1111518311:11(5183)Online publication date: 2-Jun-2021
https://doi.org/10.3390/app11115183
Sun XZhou TWang RDuan YBo LChang J(2021)Experience report: investigating bug fixes in machine learning frameworks/librariesFrontiers of Computer Science10.1007/s11704-020-9441-115:6Online publication date: 18-Jul-2021
https://doi.org/10.1007/s11704-020-9441-1
Goyal ASardana N(2020)Analytical Study on Bug Triaging PracticesCognitive Analytics10.4018/978-1-7998-2460-2.ch088(1698-1725)Online publication date: 2020
https://doi.org/10.4018/978-1-7998-2460-2.ch088
Sajedi-Badashian AStroulia E(2020)Guidelines for evaluating bug-assignment researchJournal of Software: Evolution and Process10.1002/smr.2250(e2250)Online publication date: 3-Mar-2020
https://doi.org/10.1002/smr.2250
Guo SChen SWang SZhang DLiu YGuo CLi HLi T(2019)A Multi-Factor Approach for Selection of Developers to Fix Bugs in a ProgramApplied Sciences10.3390/app91633279:16(3327)Online publication date: 13-Aug-2019
https://doi.org/10.3390/app9163327
Sun XZhou TLi GHu JYang HLi B(2017)An Empirical Study on Real Bugs for Machine Learning Programs2017 24th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC.2017.41(348-357)Online publication date: Dec-2017
https://doi.org/10.1109/APSEC.2017.41
Goyal ASardana N(2016)Analytical Study on Bug Triaging PracticesInternational Journal of Open Source Software and Processes10.4018/IJOSSP.20160401027:2(20-42)Online publication date: Apr-2016
https://doi.org/10.4018/IJOSSP.2016040102

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