• DocumentCode
    1691521
  • Title

    Architectural design recovery using data mining techniques

  • Author

    Sartipi, Kamran ; Kontogiannis, Kostas ; Mavaddat, Farhad

  • Author_Institution
    Dept. of Comput. Sci., Waterloo Univ., Ont., Canada
  • fYear
    2000
  • fDate
    2/1/2000 12:00:00 AM
  • Firstpage
    129
  • Lastpage
    139
  • Abstract
    The paper presents a technique for recovering the high level design of legacy software systems according to user defined architectural plans. Architectural plans are represented using a description language and specify system components and their interfaces. Such descriptions are viewed as queries that are applied on a large database which stores information extracted from the source code of the subject legacy system. Data mining techniques and a modified branch and bound search algorithm are used to control the matching process, by which the query is satisfied and query variables are instantiated. The matching process allows the alternative results to be ranked according to data mining associations and clustering techniques and, finally, be presented to the user
  • Keywords
    data mining; software architecture; software maintenance; system recovery; tree searching; architectural design recovery; branch and bound search algorithm; clustering techniques; data mining associations; data mining techniques; description language; high level design; information extraction; large database; legacy software systems; matching process; query variables; source code; subject legacy system; system components; user defined architectural plans; Clustering algorithms; Computer science; Concrete; Control systems; Data mining; Design engineering; Engines; Pattern matching; Process control; Software maintenance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance and Reengineering, 2000. Proceedings of the Fourth European
  • Conference_Location
    Zurich
  • Print_ISBN
    0-7695-0546-5
  • Type

    conf

  • DOI
    10.1109/CSMR.2000.827321
  • Filename
    827321