Do More Experienced Developers Introduce Fewer Bugs?

  • Daniel Izquierdo-Cortázar
  • Gregorio Robles
  • Jesús M. González-Barahona
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 378)


Developer experience is a common matter of study in the software maintenance and evolution research literature. However it is still not well understood if less experienced developers are more prone to introduce errors in the source code than their more experienced colleagues. This paper aims to study the relationships between experience and the bug introduction ratio using the Mozilla community as case of study.

As results, statistical differences among developers with different levels of experience has not been observed, when the expected result would have been the opposite.


  1. 1.
    Ahsan, S.N., Afzal, M.T., Zaman, S., Gütel, C., Wotawa, F.: Mining effort data from the oss repository of developer’s bug fix activity. Journal of Information Technology in Asia 3, 67–80 (2010)Google Scholar
  2. 2.
    Eyolfson, J., Tan, L., Lam, P.: Do time of day and developer experience affect commit bugginess. In: Proceeding of the 8th Working Conference on Mining Software Repositories, MSR 2011, pp. 153–162. ACM, New York (2011)CrossRefGoogle Scholar
  3. 3.
    Fritz, T., Murphy, G.C., Hill, E.: Does a programmer’s activity indicate knowledge of code? In: Proceedings of the the 6th ESEC-FSE, pp. 341–350. ACM, New York (2007)Google Scholar
  4. 4.
    German, D.M.: Using software trails to reconstruct the evolution of software: Research articles. J. Softw. Maint. Evol. 16, 367–384 (2004)CrossRefGoogle Scholar
  5. 5.
    González-Barahona, J.M., Robles, G.: On the reproducibility of empirical software engineering studies based on data retrieved from development repositories. Empirical Software Engineering 17(1-2), 75–89 (2012)CrossRefGoogle Scholar
  6. 6.
    Kim, S., Whitehead Jr., E.J., Zhang, Y.: Classifying software changes: Clean or buggy? IEEE TSE 34(2), 181–196 (2008)Google Scholar
  7. 7.
    Minto, S., Murphy, G.C.: Recommending emergent teams. In: Proceedings of the 4th International Workshop on MSR, p. 5 (2007)Google Scholar
  8. 8.
    Mockus, A., Herbsleb, J.D.: Expertise browser: a quantitative approach to identifying expertise. In: Proc of the 24rd ICSE, pp. 503–512 (May 2002)Google Scholar
  9. 9.
    Śliwerski, J., Zimmermann, T., Zeller, A.: When do changes induce fixes? In: Intl. Workshop Mining Software Repositories, pp. 1–5 (2005)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Daniel Izquierdo-Cortázar
    • 1
  • Gregorio Robles
    • 1
  • Jesús M. González-Barahona
    • 1
  1. 1.GSyC/LibreSoftUniversidad Rey Juan CarlosSpain

Personalised recommendations