• DocumentCode
    1951657
  • Title

    Extracting Prime Business Rules from Large Legacy System

  • Author

    Wang, Chengliang ; Zhou, Yaxin ; Chen, Juanjuan

  • Author_Institution
    Coll. of Comput. Sci. & Eng., Chongqing Univ., Chongqing
  • Volume
    2
  • fYear
    2008
  • fDate
    12-14 Dec. 2008
  • Firstpage
    19
  • Lastpage
    23
  • Abstract
    Business rules are operational rules that business organizations follow to perform various activities. Over time, business rules evolve and the software that implemented them is also changed. As the encompassing software becomes large and aged, the business rules embedded are substantial and difficult to extract. Furthermore, the encompassing software is changed without changing the corresponding documents, and thus often the organizations trust the code more than any other documents. It is possible to use a generic tool to extract all business rules of system however this may be an expensive exercise due to thousands upon thousands code. This paper proposes a tailored solution approach to the rule extraction problem, which consists of prime program slicing, prime domain variable identifying and data analysis, rules validation. The proposed approach has been implemented as a system and successfully experimented in a large complex financial system.
  • Keywords
    business data processing; program slicing; software maintenance; business organizations; data analysis; large legacy system; operational rules; prime business rules; prime domain variable identification; prime program slicing; rule extraction problem; rules validation; Computer science; Data analysis; Data mining; Educational institutions; Information technology; Organizational aspects; Physics computing; Programming profession; Software engineering; Software maintenance; degree of contribution; degree of effect; prime business rule extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Software Engineering, 2008 International Conference on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3336-0
  • Type

    conf

  • DOI
    10.1109/CSSE.2008.497
  • Filename
    4721993