• DocumentCode
    2726644
  • Title

    ACCD: an algorithm for comprehension-driven clustering

  • Author

    Tzerpos, Vassilios ; Holt, R.C.

  • Author_Institution
    Toronto Univ., Ont., Canada
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    258
  • Lastpage
    267
  • Abstract
    The software clustering literature contains many different approaches that attempt to automatically decompose software systems. These approaches commonly utilize criteria or measures based on principles such as high cohesion and low coupling, information hiding etc. We present an algorithm that subscribes to a philosophy targeted towards program comprehension and based on subsystem patterns. We discuss the algorithm´s implementation and describe experiments that demonstrate its usefulness
  • Keywords
    pattern clustering; reverse engineering; software engineering; statistical analysis; ACCD; automatic software system decomposition; comprehension-driven clustering algorithm; high cohesion; information hiding; low coupling; program comprehension; software clustering; subsystem patterns; Biology; Clustering algorithms; Computer industry; Psychology; Software algorithms; Software engineering; Software performance; Software systems; Statistics; Taxonomy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reverse Engineering, 2000. Proceedings. Seventh Working Conference on
  • Conference_Location
    Brisbane, Qld.
  • ISSN
    1095-1350
  • Print_ISBN
    0-7695-0881-2
  • Type

    conf

  • DOI
    10.1109/WCRE.2000.891477
  • Filename
    891477