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Are tweets useful in the bug fixing process? An empirical study on Firefox and Chrome

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Abstract

When encountering an issue, technical users (e.g., developers) usually file the issue report to the issue tracking systems. But non-technical end-users are more likely to express their opinions on social network platforms, such as Twitter. For software systems (e.g., Firefox and Chrome) that have a high exposure to millions of non-technical end-users, it is important to monitor and solve issues observed by a large user base. The widely used micro-blogging site (i.e., Twitter) has millions of active users. Therefore, it can provide instant feedback on products to the developers. In this paper, we investigate whether social networks (i.e., Twitter) can improve the bug fixing process by analyzing the short messages posted by end-users on Twitter (i.e., tweets). We propose an approach to remove noisy tweets, and map the remaining tweets to bug reports. We conduct an empirical study to investigate the usefulness of Twitter in the bug fixing process. We choose two widely adopted browsers (i.e., Firefox and Chrome) that are also large and rapidly released software systems. We find that issue reports are not treated differently regardless whether users tweet about the issue or not, except that Firefox developers tend to label an issue as more severe if users tweet about it. The feedback from Firefox contributors confirms that the tweets are not currently leveraged in the bug fixing process, due to the challenges associated to discovering bugs through Twitter. Moreover, we observe that many issues are posted on Twitter earlier than on issue tracking systems. More specifically, at least one third of issues could have been reported to developers 8.2 days and 7.6 days earlier in Firefox and Chrome, respectively. In conclusion, tweets are useful in providing earlier acknowledgment of issues, which developers can potentially use to focus their efforts on the issues impacting a large user-base.

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Notes

  1. According to W3Schools’ browser statistics in March 2016, Chrome ranks the first with 69.9% of the usage share of browsers, followed by Firefox that has approximately 17.8% of worldwide usage share of the browsers. URL: http://www.w3schools.com/browsers/browsers_stats.asp

  2. https://en.wikipedia.org/wiki/History_of_Firefox

  3. https://en.wikipedia.org/wiki/Google_Chrome_release_history

  4. https://www.chromium.org/for-testers/bug-reporting-guidelines

  5. https://www.bugzilla.org/

  6. https://bugs.chromium.org/p/chromium/issues/list

  7. http://icon.shef.ac.uk/Moby/mwords.html

  8. https://github.com/mariamelm2/TwitterPaperRep/blob/master/Data/stop_words.txt

  9. https://twitter.com/

  10. http://www.internetlivestats.com/twitter-statistics

  11. http://www.socialmediatoday.com/content/top-twitter-abbreviations-you-need-know

  12. http://www.webopedia.com/quick_ref/Twitter_Dictionary_Guide.asp

  13. http://www.noslang.com/twitterslang.php,searchcrm.techtarget.com/definition/Twitter-chat-and-text-messaging-abbreviations

  14. http://marketing.wtwhmedia.com/30-must-know-twitter-abbreviations-and-acronyms/

  15. https://digiphile.wordpress.com/2009/06/11/top-50-twitter-acronyms-abbreviations-and-initialisms/

  16. https://www.surveysystem.com/sscalc.htm

  17. http://projects.csail.mit.edu/spatial/Stanford_Parser

  18. https://nlp.stanford.edu/software/dependencies_manual.pdf

  19. http://www.nltk.org/

  20. http://lucene.apache.org/core/5_3_1/

  21. https://lucene.apache.org/core/5_3_1/core/org/apache/lucene/search/similarities/TFIDFSimilarity.html

  22. https://www.surveysystem.com/sscalc.htm

  23. https://cran.r-project.org/web/packages/ldatuning

  24. https://support.mozilla.org/en-US/

  25. https://groups.google.com/a/chromium.org/forum/#!forum/chromium-dev

  26. https://bugzilla.mozilla.org/show_bug.cgi?id=1361468

  27. https://bugzilla.mozilla.org/show_bug.cgi?id=1361498

  28. https://github.com/mariamelm2/TwitterPaperRep

  29. https://twitter.com/

  30. https://www.tumblr.com/

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Authors and Affiliations

  1. School of Computing, Queen’s University, Kingston, ON, Canada

    Mariam El Mezouar & Feng Zhang

  2. Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON, Canada

    Ying Zou

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  1. Mariam El Mezouar
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  2. Feng Zhang
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  3. Ying Zou
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Correspondence to Mariam El Mezouar.

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Communicated by: David Lo

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Mezouar, M., Zhang, F. & Zou, Y. Are tweets useful in the bug fixing process? An empirical study on Firefox and Chrome. Empir Software Eng 23, 1704–1742 (2018). https://doi.org/10.1007/s10664-017-9559-4

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