• DocumentCode
    356826
  • Title

    Data mining library reuse patterns using generalized association rules

  • Author

    Michail, Amir

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Washington Univ., Seattle, WA, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    167
  • Lastpage
    176
  • Abstract
    It is shown how data mining can be used to discover library reuse patterns in existing applications. Specifically, we consider the problem of discovering library classes and member functions that are typically reused in combination by application classes. The paper improves upon earlier research using “association rules” (A. Michail, 1999) by taking into account the inheritance hierarchy using “generalized association rules”. This turns out to be a non-trivial but worthwhile endeavor. By browsing generalized association rules, a developer can discover patterns in library usage in a way that takes into account inheritance relationships. For example, such a rule might tell us that application classes that inherit from a particular library class often instantiate another class or one of its descendents. We illustrate the approach using our tool, CodeWeb, by demonstrating characteristic ways in which applications reuse classes in the KDE application framework
  • Keywords
    data mining; inheritance; object-oriented programming; software libraries; software reusability; CodeWeb; KDE application framework; application classes; association rules; data mining; generalized association rules; inheritance hierarchy; inheritance relationships; library class; library classes; library reuse patterns; member functions; software libraries; Application software; Association rules; Computer science; Data engineering; Data mining; Open source software; Paints; Permission; Software libraries; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, 2000. Proceedings of the 2000 International Conference on
  • Conference_Location
    Limerick
  • ISSN
    0270-5257
  • Print_ISBN
    1-58113-206-9
  • Type

    conf

  • DOI
    10.1109/ICSE.2000.870408
  • Filename
    870408