short-paper

An alternative issue tracking dataset of public Jira repositories

Authors:

Lloyd Montgomery,

Walid MaalejAuthors Info & Claims

MSR '22: Proceedings of the 19th International Conference on Mining Software Repositories

Pages 73 - 77

https://doi.org/10.1145/3524842.3528486

Published: 17 October 2022 Publication History

Abstract

Organisations use issue tracking systems (ITSs) to track and document their projects' work in units called issues. This style of documentation encourages evolutionary refinement, as each issue can be independently improved, commented on, linked to other issues, and progressed through the organisational workflow. Commonly studied ITSs so far include GitHub, GitLab, and Bugzilla, while Jira, one of the most popular ITS in practice with a wealth of additional information, has yet to receive similar attention. Unfortunately, diverse public Jira datasets are rare, likely due to the difficulty in finding and accessing these repositories. With this paper, we release a dataset of 16 public Jiras with 1822 projects, spanning 2.7 million issues with a combined total of 32 million changes, 9 million comments, and 1 million issue links. We believe this Jira dataset will lead to many fruitful research projects investigating issue evolution, issue linking, cross-project analysis, as well as cross-tool analysis when combined with existing well-studied ITS datasets.

References

[1]

Gabriele Bavota and Barbara Russo. 2016. A large-scale empirical study on self-admitted technical debt. In Proceedings of the 13th international conference on mining software repositories. Association for Computing Machinery, New York, NY, USA, 315--326.

Digital Library

[2]

Nicolas Bettenburg, Sascha Just, Adrian Schröter, Cathrin Weiss, Rahul Premraj, and Thomas Zimmermann. 2008. What makes a good bug report?. In Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering. Association for Computing Machinery, New York,NY, USA, 308--318.

Digital Library

[3]

Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77--101.

[4]

D. S. Cruzes and T. Dyba. 2011. Recommended Steps for Thematic Synthesis in Software Engineering. In 2011 International Symposium on Empirical Software Engineering and Measurement. IEEE Computer Society, Banff, Alberta, Canada, 275--284.

Digital Library

[5]

J. Deshmukh, K. M. Annervaz, S. Podder, S. Sengupta, and N. Dubash. 2017. Towards Accurate Duplicate Bug Retrieval Using Deep Learning Techniques. In 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, Shanghai, China, 115--124.

[6]

N. A. Ernst and G. C. Murphy. 2012. Case Studies in Just-in-Time Requirements Analysis. In 2012 Second IEEE International Workshop on Empirical Requirements Engineering (EmpiRE). IEEE, Chicago, IL, USA, 25--32.

[7]

Camilo Fitzgerald, Emmanuel Letier, and Anthony Finkelstein. 2012. Early failure prediction in feature request management systems. In 2011 IEEE 19th International Requirements Engineering Conference. IEEE, Springer, Chicago, Illinois, USA, 229--238.

[8]

Jianjun He, Ling Xu, Meng Yan, Xin Xia, and Yan Lei. 2020. Duplicate Bug Report Detection Using Dual-Channel Convolutional Neural Networks. In Proceedings of the 28th International Conference on Program Comprehension (Seoul, Republic of Korea) (ICPC '20). Association for Computing Machinery, New York, NY, USA, 117--127.

Digital Library

[9]

Petra Heck and Andy Zaidman. 2013. An Analysis of Requirements Evolution in Open Source Projects: Recommendations for Issue Trackers. In Proceedings of the 2013 International Workshop on Principles of Software Evolution (IWPSE 2013). Association for Computing Machinery, New York, NY, USA, 43--52.

Digital Library

[10]

Kim Herzig, Sascha Just, and Andreas Zeller. 2013. It's not a bug, it's a feature: How misclassification impacts bug prediction. In 2013 35th International Conference on Software Engineering (ICSE). IEEE Press, San Francisco, CA, USA, 392--401.

[11]

Gaeul Jeong, Sunghun Kim, and Thomas Zimmermann. 2009. Improving Bug Triage with Bug Tossing Graphs. In 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME) (Amsterdam, The Netherlands) (ESEC/FSE '09). Association for Computing Machinery, New York, NY, USA, 111--120.

Digital Library

[12]

Ahmed Lamkanfi, Serge Demeyer, Emanuel Giger, and Bart Goethals. 2010. Predicting the severity of a reported bug. In 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010). IEEE, IEEE, Cape Town, South Africa, 1--10.

[13]

Ahmed Lamkanfi, Serge Demeyer, Quinten David Soetens, and Tim Verdonck. 2011. Comparing mining algorithms for predicting the severity of a reported bug. In 2011 15th European Conference on Software Maintenance and Reengineering. IEEE, IEEE Computer Society, USA, 249--258.

Digital Library

[14]

Thorsten Merten, Matúš Falis, Paul Hübner, Thomas Quirchmayr, Simone Bürsner, and Barbara Paech. 2016. Software Feature Request Detection in Issue Tracking Systems. In 2016 IEEE 24th International Requirements Engineering Conference (RE). IEEE, Beijing, China, 166--175.

[15]

Lloyd Montgomery and Daniela Damian. 2017. Customer support ticket escalation prediction using feature engineering. In 2017 IEEE 25th international requirements engineering conference (RE). IEEE, IEEE, USA, 362--371.

[16]

Marco Ortu, Giuseppe Destefanis, Bram Adams, Alessandro Murgia, Michele Marchesi, and Roberto Tonelli. 2015. The jira repository dataset: Understanding social aspects of software development. In Proceedings of the 11th international conference on predictive models and data analytics in software engineering. Association for Computing Machinery, New York, NY, USA, 1--4.

Digital Library

[17]

Marco Ortu, Alessandro Murgia, Giuseppe Destefanis, Parastou Tourani, Roberto Tonelli, Michele Marchesi, and Bram Adams. 2016. The emotional side of software developers in JIRA. In 2016 IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR). IEEE, IEEE, Austin, Texas, USA, 480--483.

Digital Library

[18]

Werner Reinartz, Manfred Krafft, and Wayne D Hoyer. 2004. The customer relationship management process: Its measurement and impact on performance. Journal of marketing research 41, 3 (2004), 293--305.

[19]

Igor Steinmacher, Christoph Treude, and Marco Aurelio Gerosa. 2018. Let me in: Guidelines for the successful onboarding of newcomers to open source projects. IEEE Software 36, 4 (2018), 41--49.

[20]

Xiaoyin Wang, Lu Zhang, Tao Xie, John Anvik, and Jiasu Sun. 2008. An Approach to Detecting Duplicate Bug Reports Using Natural Language and Execution Information. In Proceedings of the 30th International Conference on Software Engineering (Leipzig, Germany) (ICSE '08). Association for Computing Machinery, New York, NY, USA, 461--470.

Digital Library

[21]

Laerte Xavier, Fabio Ferreira, Rodrigo Brito, and Marco Tulio Valente. 2020. Beyond the code: Mining self-admitted technical debt in issue tracker systems. In Proceedings of the 17th International Conference on Mining Software Repositories. IEEE, USA, 137--146.

Digital Library

[22]

Thomas Zimmermann, Rahul Premraj, Nicolas Bettenburg, Sascha Just, Adrian Schröter, and Cathrin Weiss. 2010. What Makes a Good Bug Report? IEEE Transactions on Software Engineering 36, 5 (2010), 618--643.

Digital Library

Cited By

Colavito GLanubile FNovielli NQuaranta L(2024)Impact of data quality for automatic issue classification using pre-trained language modelsJournal of Systems and Software10.1016/j.jss.2023.111838210:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.jss.2023.111838
Hu MLin ZMarshall A(2024)Issue Links Retrieval for New Issues in Issue Tracking SystemsNatural Language Processing and Information Systems10.1007/978-3-031-70242-6_13(126-138)Online publication date: 20-Sep-2024
https://doi.org/10.1007/978-3-031-70242-6_13
Reszka ŁSosnowski JDobrzyński B(2023)Enhancing Software Project Monitoring with Multidimensional Data Repository MiningElectronics10.3390/electronics1218377412:18(3774)Online publication date: 6-Sep-2023
https://doi.org/10.3390/electronics12183774
Show More Cited By

Recommendations

The JIRA Repository Dataset: Understanding Social Aspects of Software Development
PROMISE '15: Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering

Issue tracking systems store valuable data for testing hypotheses concerning maintenance, building statistical prediction models and recently investigating developers "affectiveness". In particular, the Jira Issue Tracking System is a proprietary ...
Automated issue assignment using topic modelling on Jira issue tracking data
Abstract
As more and more software teams use online issue tracking systems to collaborate on software projects, the accurate assignment of new issues to the most suitable contributors may have significant impact on the success of the project. As a result, ...

In this work, we provide a methodology for automated issue assignment, designed using Jira issue tracking data extracted from the Apache Software Foundation that describe both features and bugs. Our methodology employs topic modelling to extract the ...
Hands-On Agile Software Development with JIRA: Design and manage software projects using the Agile methodology

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MSR '22: Proceedings of the 19th International Conference on Mining Software Repositories

May 2022

815 pages

ISBN:9781450393034

DOI:10.1145/3524842

General Chair:
David Lo
Singapore Management University, Singapore
,
Program Chairs:
Shane McIntosh
University of Waterloo, Canada
,
Nicole Novielli
University of Bari, Italy

Copyright © 2022 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 the author(s) 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

SIGSOFT: ACM Special Interest Group on Software Engineering

In-Cooperation

IEEE CS

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Short-paper

Funding Sources

European Union Horizon 2020 Research and Innovation programme
Natural Sciences and Engineering Research Council of Canada (NSERC)

Conference

MSR '22

Sponsor:

SIGSOFT

MSR '22: 19th International Conference on Mining Software Repositories

May 23 - 24, 2022

Pennsylvania, Pittsburgh

Upcoming Conference

ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

14
Total Citations
View Citations
358
Total Downloads

Downloads (Last 12 months)119
Downloads (Last 6 weeks)11

Reflects downloads up to 10 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Colavito GLanubile FNovielli NQuaranta L(2024)Impact of data quality for automatic issue classification using pre-trained language modelsJournal of Systems and Software10.1016/j.jss.2023.111838210:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.jss.2023.111838
Hu MLin ZMarshall A(2024)Issue Links Retrieval for New Issues in Issue Tracking SystemsNatural Language Processing and Information Systems10.1007/978-3-031-70242-6_13(126-138)Online publication date: 20-Sep-2024
https://doi.org/10.1007/978-3-031-70242-6_13
Reszka ŁSosnowski JDobrzyński B(2023)Enhancing Software Project Monitoring with Multidimensional Data Repository MiningElectronics10.3390/electronics1218377412:18(3774)Online publication date: 6-Sep-2023
https://doi.org/10.3390/electronics12183774
Zhang THan DVinayakarao VIrsan IXu BThung FLo DJiang L(2023)Duplicate Bug Report Detection: How Far Are We?ACM Transactions on Software Engineering and Methodology10.1145/357604232:4(1-32)Online publication date: 27-May-2023
https://dl.acm.org/doi/10.1145/3576042
Skryseth DShivashankar KPilán IMartini A(2023)Technical Debt Classification in Issue Trackers using Natural Language Processing based on Transformers2023 ACM/IEEE International Conference on Technical Debt (TechDebt)10.1109/TechDebt59074.2023.00017(92-101)Online publication date: May-2023
https://doi.org/10.1109/TechDebt59074.2023.00017
Coremans BKlomp ARukmono SKrüger JFahland DChaudron M(2023)Process Mining from Jira Issues at a Large Company2023 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME58846.2023.00055(425-435)Online publication date: 1-Oct-2023
https://doi.org/10.1109/ICSME58846.2023.00055
Zhou HWang TZhang YShen Y(2023)TLDBERT: Leveraging Further Pre-Trained Model for Issue Typed Links Detection2023 30th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC60848.2023.00077(594-598)Online publication date: 4-Dec-2023
https://doi.org/10.1109/APSEC60848.2023.00077
Lüders CPietz TMaalej W(2023)On understanding and predicting issue linksRequirements Engineering10.1007/s00766-023-00406-x28:4(541-565)Online publication date: 21-Sep-2023
https://dl.acm.org/doi/10.1007/s00766-023-00406-x
Frattini JMontgomery LFischbach JMendez DFucci DUnterkalmsteiner M(2023)Requirements quality research: a harmonized theory, evaluation, and roadmapRequirements Engineering10.1007/s00766-023-00405-y28:4(507-520)Online publication date: 12-Aug-2023
https://dl.acm.org/doi/10.1007/s00766-023-00405-y
Maarleveld JDekker ADruyts SSoliman M(2023)Maestro: A Deep Learning Based Tool to Find and Explore Architectural Design Decisions in Issue Tracking SystemsSoftware Architecture. ECSA 2023 Tracks, Workshops, and Doctoral Symposium10.1007/978-3-031-66326-0_24(390-405)Online publication date: 18-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-66326-0_24
Show More Cited By

View Options

Get Access

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