IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v10y2019i5d10.1007_s13198-019-00850-5.html
   My bibliography  Save this article

An empirical study of non-reproducible bugs

Author

Listed:
  • Anjali Goyal

    (Jaypee Institute of Information Technology)

  • Neetu Sardana

    (Jaypee Institute of Information Technology)

Abstract

A large number of bug reports received in bug tracking system causes a negative impact on software’s growth and maintenance. Non-Reproducible bugs are an additional overhead on bug fixing process as certain percentage of Non-Reproducible bugs get fixed and these are difficult to detect. Their fixation can enhance the efficiency of bug fixing process. Past studies had ignored Non-Reproducible bugs while investigating bugs with varied perspectives. In this paper, we investigate characteristics of Non-Reproducible bug reports to understand their behaviour so that overall bug fixing process can be improved. We have also build machine learning models to predict fixable bugs from the set of Non-Reproducible marked bugs. We mine four large, open-source projects of Bugzilla repository and analyze Non-Reproducible bugs with different dimensions: frequency distribution, time-series analysis, active fix time, developer discussions, severity, priority and component. This study shows that there exists a significant number of Non-Reproducible bugs in each project and their occurrence follows a normal distribution with project longevity. They possess higher severity and lower priority as compared to reproducible bugs. Also, there exist specific components which are more prone to have non-reproducible bugs. We found that Non-Reproducible bugs consume more fixation time thereby affecting bug fixing processes’ efficiency. The overall results suggested that efforts in Non-Reproducible bugs could be minimized by developing a fixability prediction model that can build confidence among developers. Hence, we learned 52 classifiers for prediction of fixability among NR bugs. Our results show that prediction models achieved F1-Score up to 89.2%, 93.7%, 93.8% and 98.4% for NetBeans, Eclipse, Open Office and Mozilla Firefox projects respectively.

Suggested Citation

  • Anjali Goyal & Neetu Sardana, 2019. "An empirical study of non-reproducible bugs," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1186-1220, October.
    • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:5:d:10.1007_s13198-019-00850-5
    DOI: 10.1007/s13198-019-00850-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-019-00850-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-019-00850-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arvinder Kaur & Shubhra Goyal Jindal, 2019. "Text analytics based severity prediction of software bugs for apache projects," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 765-782, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ruby Chauhan & Shakshi Sharma & Anjali Goyal, 2023. "DENATURE: duplicate detection and type identification in open source bug repositories," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 275-292, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:10:y:2019:i:5:d:10.1007_s13198-019-00850-5. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.