• DocumentCode
    2155763
  • Title

    Methods for selecting and improving software clustering algorithms

  • Author

    Shtern, Mark ; Tzerpos, Vassilios

  • Author_Institution
    York Univ., Toronto, ON
  • fYear
    2009
  • fDate
    17-19 May 2009
  • Firstpage
    248
  • Lastpage
    252
  • Abstract
    Several software clustering algorithms have been proposed in the literature, each with its own strengths and weaknesses. Most of these algorithms have been applied to particular software systems with considerable success. However, the question of how to select a software clustering algorithm that is best suited for a specific software system remains unanswered. In this paper, we introduce a method for the selection of a software clustering algorithm for specific needs. The proposed method is based on a newly introduced formal description template for software clustering algorithms. Using the same template, we also introduce a method for software clustering algorithm improvement.
  • Keywords
    formal specification; pattern clustering; formal description template; software clustering algorithm selection; software system clustering algorithm improvement; Algorithm design and analysis; Clustering algorithms; Guidelines; Heuristic algorithms; Software algorithms; Software maintenance; Software quality; Software standards; Software systems; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Program Comprehension, 2009. ICPC '09. IEEE 17th International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1092-8138
  • Print_ISBN
    978-1-4244-3998-0
  • Electronic_ISBN
    1092-8138
  • Type

    conf

  • DOI
    10.1109/ICPC.2009.5090051
  • Filename
    5090051