• DocumentCode
    2339957
  • Title

    Application of active learning strategy and formalization method in requirement analysis

  • Author

    Zhang, Zhifeng ; Liu, Yuxi

  • Author_Institution
    Software Coll., Zhengzhou Univ. of Light Ind., Zhengzhou, China
  • fYear
    2012
  • fDate
    3-5 June 2012
  • Firstpage
    958
  • Lastpage
    960
  • Abstract
    On base of research and analysis for Bayesian network classifier, active learning strategy and formalization method, this paper proposed a new approach for software requirement analysis based on active learning strategy and formalization method. This approach combined of the Bayesian network, Bayesian network classifier, active learning strategy and formalization method, and improved the approach in the requirement analysis to get the better reusability and the extensibility. This approach eliminated the ambiguity, partialness, inconsistency of system, and provided a reasonable solution for uncertain problem in requirement analysis, therefore improved the performance and the quality of the software.
  • Keywords
    belief networks; formal specification; learning (artificial intelligence); Bayesian network classifier; active learning strategy; formalization method; software requirement analysis; Bayesian methods; Cognition; Educational institutions; Probabilistic logic; Programming; Software; Training; Active learning strategy; B method; Bayesian network classifier; formalization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Applications (ISRA), 2012 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4673-2205-8
  • Type

    conf

  • DOI
    10.1109/ISRA.2012.6219353
  • Filename
    6219353