research-article

Factors characterizing reopened issues: a case study

Authors:

Ayse Tosun Misirli,

Andriy Miranskyy,

Ayse BenerAuthors Info & Claims

PROMISE '12: Proceedings of the 8th International Conference on Predictive Models in Software Engineering

Pages 1 - 10

https://doi.org/10.1145/2365324.2365327

Published: 21 September 2012 Publication History

Abstract

Background: Reopened issues may cause problems in managing software maintenance effort. In order to take actions that will reduce the likelihood of issue reopening the possible causes of bug reopens should be analysed.

Aims: In this paper, we investigate potential factors that may cause issue reopening.

Method: We have extracted issue activity data from a large release of an enterprise software product. We consider four dimensions, namely developer activity, issue proximity network, static code metrics of the source code changed to fix an issue, issue reports and fixes as possible factors that may cause issue reopening. We have done exploratory analysis on data. We build logistic regression models on data in order to identify key factors leading issue reopening. We have also conducted a survey regarding these factors with the QA Team of the product and interpreted the results.

Results: Our results indicate that centrality in the issue proximity network and developer activity are important factors in issue reopening. We have also interpreted our results with the QA Team to point out potential implications for practitioners.

Conclusions: Quantitative findings of our study suggest that issue complexity and developers workload play an important role in triggering issue reopening.

References

[1]

E. Alpaydin. Introduction to Machine Learning (Adaptive Computation and Machine Learning). The MIT Press, 2004.

Digital Library

[2]

J. Anvik, L. Hiew, and G. C. Murphy. Who should fix this bug? In Proceedings of the International Conference on Software Engineering, pages 361--370, Shanghai, China, 2006.

Digital Library

[3]

J. Anvik and G. Murphy. Determining implementation expertise from bug reports. In Mining Software Repositories, 2007. ICSE Workshops MSR'07. Fourth International Workshop on, pages 1--8. IEEE, 2007.

Digital Library

[4]

J. Anvik and G. C. Murphy. Reducing the effort of bug report triage. ACM Transactions on Software Engineering and Methodology, 20(3): 1--35, Aug. 2011.

Digital Library

[5]

A. Bakir, E. Kocaguneli, A. Tosun, A. Bener, and B. Turhan. Xiruxe: An Intelligent Fault Tracking Tool. AIPR09, Orlando, 2009.

[6]

N. Bettenburg and A. Hassan. Studying the Impact of Social Structures on Software Quality. In 2010 IEEE 18th International Conference on Program Comprehension, pages 124--133. IEEE, 2010.

Digital Library

[7]

L. Briand, W. Melo, and J. Wust. Assessing the applicability of fault-proneness models across object-oriented software projects. Software Engineering, IEEE Transactions on, 28(7): 706--720, 2002.

Digital Library

[8]

B. Caglayan, A. Tosun, A. Miranskyy, A. Bener, and N. Ruffolo. Usage of multiple prediction models based on defect categories. In Proceedings of the 6th International Conference on Predictive Models in Software Engineering, pages 1--9. ACM, 2010.

Digital Library

[9]

D. Cubranic and G. Murphy. Automatic bug triage using text categorization. In Proceedings of the Sixteenth International Conference on Software Engineering Knowledge Engineering, pages 1--6. Citeseer, 2004.

[10]

A. Gelman and J. Hill. Data Analysis Using Regression And Multilevel/Hierarchical Models. Analytical Methods for Social Research. Cambridge University Press, 2007.

[11]

E. Giger, M. Pinzger, and H. Gall. Predicting the Fix Time of Bugs. In RSSE '10 Proceedings of the 2nd International Workshop on Recommendation Systems for Software Engineering, pages 52--56, 2010.

Digital Library

[12]

P. Guo, T. Zimmermann, N. Nagappan, and B. Murphy. Characterizing and predicting which bugs get fixed: An empirical study of Microsoft Windows. In Software Engineering, 2010 ACM/IEEE 32nd International Conference on, volume 1, pages 495--504. IEEE, 2010.

Digital Library

[13]

P. Guo, T. Zimmermann, N. Nagappan, and B. Murphy. Not my bug! and other reasons for software bug report reassignments. In Proceedings of the ACM 2011 conference on Computer supported cooperative work, pages 395--404. ACM, 2011.

Digital Library

[14]

J. Herbsleb and A. Mockus. An empirical study of speed and communication in globally distributed software development. IEEE Transactions on Software Engineering, 29(6): 481--494, June 2003.

Digital Library

[15]

S. Koch. Effort modeling and programmer participation in open source software projects. Information Economics and Policy, 20(4): 345--355, Dec. 2008.

[16]

S. Lessmann, B. Baesens, C. Mues, and S. Pietsch. Benchmarking classification models for software defect prediction: A proposed framework and novel findings. Software Engineering, IEEE Transactions on, 34(4): 485--496, 2008.

Digital Library

[17]

C. d. Mazancourt and V. Calcagno. glmulti: An r package for easy automated model selection with (generalized) linear models. Journal of Statistical Software, 34(i12), 2010.

[18]

A. T. Misirli, B. Caglayan, A. V. Miranskyy, A. Bener, and N. Ruffolo. Different strokes for different folks: a case study on software metrics for different defect categories. In Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics, WETSoM '11, pages 45--51, New York, NY, USA, 2011. ACM.

Digital Library

[19]

E. Shihab, A. Ihara, Y. Kamei, W. M. Ibrahim, M. Ohira, B. Adams, A. E. Hassan, and K.-i. Matsumoto. Predicting Re-opened Bugs: A Case Study on the Eclipse Project. 2010 17th Working Conference on Reverse Engineering, pages 249--258, Oct. 2010.

Digital Library

[20]

A. Tamrawi, T. Nguyen, and J. Al-Kofahi. Fuzzy set-based automatic bug triaging: NIER track. Proceedings of the 33rd International Conference on Software Engineering, pages 884--887, 2011.

Digital Library

[21]

C. Weiss, R. Premraj, T. Zimmermann, and A. Zeller. How long will it take to fix this Bug? In Fourth International Workshop on Mining Software Repositories, 2007. ICSE Workshops MSR'07, number 2, 2007.

Digital Library

[22]

E. J. Weyuker, T. J. Ostrand, and R. M. Bell. Using developer information as a factor for fault prediction. In Proceedings of the Third International Workshop on Predictor Models in Software Engineering. IEEE Computer Society, May 2007.

Digital Library

[23]

S. Zaman, B. Adams, and A. E. Hassan. Security Versus Performance Bugs: A Case Study on Firefox. Design, pages 93--102, 2011.

Digital Library

[24]

T. Zimmermann and N. Nagappan. Predicting defects with program dependencies. 2009 3rd International Symposium on Empirical Software Engineering and Measurement, pages 435--438, Oct. 2009.

Digital Library

[25]

T. Zimmermann, N. Nagappan, P. Guo, and B. Murphy. Characterizing and predicting which bugs get reopened. In Proceedings of the 34th International Conference on Software Engineering {ACCEPTED}, 2012.

Digital Library

Cited By

Kucuk BHanhan ITuzun E(2023)Characterizing duplicate bugsJournal of Software: Evolution and Process10.1002/smr.244635:11Online publication date: 2-Nov-2023
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Tagra AZhang HRajbahadur GHassan A(2022)Revisiting reopened bugs in open source software systemsEmpirical Software Engineering10.1007/s10664-022-10133-627:4Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s10664-022-10133-6
Assavakamhaenghan NChoetkiertikul MTuarob SKula RHata HRagkhitwetsagul CSunetnanta TMatsumoto K(2019)Software Team Member Configurations: A Study of Team Effectiveness in Moodle2019 10th International Workshop on Empirical Software Engineering in Practice (IWESEP)10.1109/IWESEP49350.2019.00012(19-195)Online publication date: Dec-2019
https://doi.org/10.1109/IWESEP49350.2019.00012
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Factors characterizing reopened issues: a case study

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cover image ACM Other conferences

PROMISE '12: Proceedings of the 8th International Conference on Predictive Models in Software Engineering

September 2012

126 pages

ISBN:9781450312417

DOI:10.1145/2365324

Conference Chair:
Stefan Wagner
U Stuttgart

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2012

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PROMISE '12

PROMISE '12: 8th International Conference on Predictive Models in Software Engineering

September 21 - 22, 2012

Lund, Sweden

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PROMISE '12 Paper Acceptance Rate 12 of 24 submissions, 50%;

Overall Acceptance Rate 98 of 213 submissions, 46%

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Cited By

Kucuk BHanhan ITuzun E(2023)Characterizing duplicate bugsJournal of Software: Evolution and Process10.1002/smr.244635:11Online publication date: 2-Nov-2023
https://dl.acm.org/doi/10.1002/smr.2446
Tagra AZhang HRajbahadur GHassan A(2022)Revisiting reopened bugs in open source software systemsEmpirical Software Engineering10.1007/s10664-022-10133-627:4Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1007/s10664-022-10133-6
Assavakamhaenghan NChoetkiertikul MTuarob SKula RHata HRagkhitwetsagul CSunetnanta TMatsumoto K(2019)Software Team Member Configurations: A Study of Team Effectiveness in Moodle2019 10th International Workshop on Empirical Software Engineering in Practice (IWESEP)10.1109/IWESEP49350.2019.00012(19-195)Online publication date: Dec-2019
https://doi.org/10.1109/IWESEP49350.2019.00012
Anwar HPfahl D(2017)Towards Greener Software Engineering Using Software Analytics: A Systematic Mapping2017 43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA.2017.56(157-166)Online publication date: Aug-2017
https://doi.org/10.1109/SEAA.2017.56
Zhao YZhang FShihab EZou YHassan AGenero MJedlitschka AJørgensen MScanniello GSampath SCaivano DPort D(2016)How Are Discussions Associated with Bug Reworking?Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/2961111.2962591(1-10)Online publication date: 8-Sep-2016
https://dl.acm.org/doi/10.1145/2961111.2962591
Ortu MMurgia ADestefanis GTourani PTonelli RMarchesi MAdams BKim MRobbes RBird C(2016)The emotional side of software developers in JIRAProceedings of the 13th International Conference on Mining Software Repositories10.1145/2901739.2903505(480-483)Online publication date: 14-May-2016
https://dl.acm.org/doi/10.1145/2901739.2903505
Misirli AShihab EKamei Y(2016)Studying high impact fix-inducing changesEmpirical Software Engineering10.1007/s10664-015-9370-z21:2(605-641)Online publication date: 1-Apr-2016
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Ortu MDestefanis GAdams BMurgia AMarchesi MTonelli RBener AMinku LTurhan B(2015)The JIRA Repository DatasetProceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/2810146.2810147(1-4)Online publication date: 21-Oct-2015
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Çağlayan BBener AMiranskyy ASharp HPrikladnicki RBegel Ade Souza C(2014)Factors affecting team evolution during software projectsProceedings of the 7th International Workshop on Cooperative and Human Aspects of Software Engineering10.1145/2593702.2593715(16-23)Online publication date: 2-Jun-2014
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Pan JMao X(2014)An Empirical Study on Interaction Factors Influencing Bug ReopeningsProceedings of the 2014 21st Asia-Pacific Software Engineering Conference - Volume 0210.1109/APSEC.2014.90(39-42)Online publication date: 1-Dec-2014
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