Issue Dynamics in Github Projects

  • Riivo KikasEmail author
  • Marlon Dumas
  • Dietmar Pfahl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9459)


Issue repositories are used to keep of track of bugs, development tasks and feature requests in software development projects. In the case of open source projects, everyone can submit a new issue in the tracker. This practice can lead to situations where more issues are created than what can be effectively handled by the project members, raising the question of how issues are treated as the capacity of the project members is exceeded. In this paper, we study the temporal dynamics of issues in a popular open source development platform, namely Github, based on a sample of 4000 projects. We specifically analyze how the rate of issue creation, the amount of pending issues, and their average lifetime evolve over the course of time. The results show that more issues are opened shortly after the creation of a project repository and that the amount of pending issues increases inexorably due to forgotten (unclosed) issues. Yet, the average issue lifetime (for issues that do get closed) is relatively stable over time. These observations suggest that Github projects have implicit mechanisms for handling issues perceived to be important to the project, while neglecting those that exceed the project’s capacity.



This research was supported by the Estonian Research Council and by ERDF via the Software Technology and Applications Competence Centre - STACC.


  1. 1.
    Bertram, D., Voida, A., Greenberg, S., Walker, R.: Communication, collaboration, and bugs: the social nature of issue tracking in small, collocated teams. In: Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, pp. 291–300. ACM, Savannah (2010)Google Scholar
  2. 2.
    Bissyande, T.F., Lo, D., Jiang, L., Reveillere, L., Klein, J., Le Traon, Y.: Got issues? Who cares about it? A large scale investigation of issue trackers from github. In: 2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE), pp. 188–197. IEEE (2013)Google Scholar
  3. 3.
    Cabot, J., Canovas Izquierdo, J.L., Cosentino, V., Rolandi, B.: Exploring the use of labels to categorize issues in open-source software projects. In: 2015 IEEE 22nd International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 550–554. IEEE (2015)Google Scholar
  4. 4.
    Crowston, K., Annabi, H., Howison, J.: Defining open source software project success. In: ICIS 2003 Proceedings, p. 28 (2003)Google Scholar
  5. 5.
    Garousi, V.: Evidence-based insights about issue management processes: an exploratory study. In: Wang, Q., Garousi, V., Madachy, R., Pfahl, D. (eds.) ICSP 2009. LNCS, vol. 5543, pp. 112–123. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  6. 6.
    Giger, E., Pinzger, M., Gall, H.: Predicting the fix time of bugs. In: Proceedings of the 2nd International Workshop on Recommendation Systems for Software Engineering, pp. 52–56. ACM (2010)Google Scholar
  7. 7.
    Gousios, G., Spinellis, D.: Ghtorrent: Github’s data from a firehose. In: 2012 9th IEEE Working Conference on Mining Software Repositories (MSR), pp. 12–21. IEEE (2012)Google Scholar
  8. 8.
    Grammel, L., Schackmann, H., Schröter, A., Treude, C., Storey, M.A.: Attracting the community’s many eyes: an exploration of user involvement in issue tracking. In: Human Aspects of Software Engineering, p. 3. ACM (2010)Google Scholar
  9. 9.
    Izquierdo, J.L.C., Cosentino, V., Rolandi, B., Bergel, A., Cabot, J.: Gila: Github label analyzer. In: 2015 IEEE 22nd International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 479–483. IEEE (2015)Google Scholar
  10. 10.
    Kenmei, B., Antoniol, G., Di Penta, M.: Trend analysis and issue prediction in large-scale open source systems. In: 2008 12th European Conference on Software Maintenance and Reengineering, CSMR 2008, pp. 73–82. IEEE (2008)Google Scholar
  11. 11.
    Ko, A.J., Chilana, P.K.: How power users help and hinder open bug reporting. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1665–1674. ACM (2010)Google Scholar
  12. 12.
    Marks, L., Zou, Y., Hassan, A.E.: Studying the fix-time for bugs in large open source projects. In: Proceedings of the 7th International Conference on Predictive Models in Software Engineering, p. 11. ACM (2011)Google Scholar
  13. 13.
    Weiss, C., Premraj, R., Zimmermann, T., Zeller, A.: How long will it take to fix this bug? In: Proceedings of the Fourth International Workshop on Mining Software Repositories, p. 1. IEEE Computer Society (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institute of Computer ScienceUniversity of TartuTartuEstonia

Personalised recommendations