• DocumentCode
    1928623
  • Title

    Evaluating similarity measures for software decompositions

  • Author

    Wen, Zhihua ; Tzerpos, Vassilios

  • Author_Institution
    York Univ., Toronto, Ont., Canada
  • fYear
    2004
  • fDate
    11-14 Sept. 2004
  • Firstpage
    368
  • Lastpage
    377
  • Abstract
    One of the central questions that a similarity measure for software decompositions has to address is whether to consider discrepancies in terms of the nodes of a particular decomposition, or assess similarity based on differences in clustering the edges of the system´s dependency graph. We argue that considering nodes or edges in isolation is too one-sided. We outline shortcomings of previous approaches, and introduce the first dissimilarity measure that takes both nodes and edges into account. We also present experiments on real and synthetic data sets that illustrate the differences between various measures.
  • Keywords
    software metrics; software performance evaluation; edge clustering; similarity measure evaluation; software decomposition; system dependency graph; Benchmark testing; Clustering algorithms; Information retrieval; Particle measurements; Software algorithms; Software maintenance; Software measurement; Software systems; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance, 2004. Proceedings. 20th IEEE International Conference on
  • ISSN
    1063-6773
  • Print_ISBN
    0-7695-2213-0
  • Type

    conf

  • DOI
    10.1109/ICSM.2004.1357822
  • Filename
    1357822