• DocumentCode
    1200895
  • Title

    Comments on "More success and failure factors in software reuse"

  • Author

    Morisio, Maurizio ; Ezran, Michel ; Tully, Colin

  • Author_Institution
    Dipt. di Automatica e Informatica, Politecnico di Torino, Italy
  • Volume
    29
  • Issue
    5
  • fYear
    2003
  • fDate
    5/1/2003 12:00:00 AM
  • Firstpage
    478
  • Abstract
    For original paper see ibid., p. 474. This is a clear example of how research in software engineering can progress when empirical methods are applied. Menzies and Di Stefano apply a number of data mining tools to the data set. While, inmost cases, their results are in agreement with ours, in some cases they are not. Our first and main observation is that our interpretation of the data set is based not only on the data set itself but also on the knowledge gathered during the interviews with project members. The main problem with the data set is its size: 23 data points. Although this data set is the largest one available about reuse projects, it is too limited to base analysis only on data mining techniques; data mining is usually applied to data sets with thousands if not millions of data points.
  • Keywords
    data mining; software reusability; data mining; data set; software engineering; software reuse; Association rules; Computer Society; Data analysis; Data mining; Human factors; Predictive models; Production; Software engineering; Testing;
  • fLanguage
    English
  • Journal_Title
    Software Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-5589
  • Type

    jour

  • DOI
    10.1109/TSE.2003.1199077
  • Filename
    1199077