• DocumentCode
    2578265
  • Title

    Reconstructing Architectural Views from Legacy Systems

  • Author

    Boussaidi, G.E. ; Belle, Alvine Boaye ; Vaucher, Stéphane ; Mili, Hafedh

  • Author_Institution
    Dept. of Software & IT Eng., Ecole de Technol. Super., Montreal, QC, Canada
  • fYear
    2012
  • fDate
    15-18 Oct. 2012
  • Firstpage
    345
  • Lastpage
    354
  • Abstract
    Modernizing a large legacy system is a demanding and costly process which requires a deep understanding of the system´s architecture and its components. However legacy systems are poorly documented and they have often undergone many changes that make them deviate from their initial architectural design. Approaches for reconstructing architectural views from legacy systems and re-documenting the resulting components are of great value in the context of a modernization process. In this paper, we propose an approach that helps constructing distinct architectural views from legacy systems. To do so, we propose various clustering algorithms which are driven by common architectural views and styles. Our approach makes use of the knowledge discovery model which provides a standard machine-independent representation of legacy systems. We implemented and applied the approach in an industrial setting. The preliminary experimentations have shown that the algorithms perform well and produce comprehensive views.
  • Keywords
    data mining; pattern clustering; software architecture; software maintenance; architectural design; architectural view reconstruction; clustering algorithms; component redocumentation; knowledge discovery model; legacy systems; standard machine-independent representation; Aging; Clustering algorithms; Computer architecture; Partitioning algorithms; Software; Software algorithms; Standards; architectural views; architecture reconstruction; legacy system modernization; software clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reverse Engineering (WCRE), 2012 19th Working Conference on
  • Conference_Location
    Kingston, ON
  • ISSN
    1095-1350
  • Print_ISBN
    978-1-4673-4536-1
  • Type

    conf

  • DOI
    10.1109/WCRE.2012.44
  • Filename
    6385130