• DocumentCode
    2860734
  • Title

    An Improving Approach for Recovering Requirements-to-Design Traceability Links

  • Author

    Di, Fangshu ; Zhang, Maolin

  • Author_Institution
    Comput. Sci. Dept., Beihang Univ., Beijing, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Requirement tracing is an important activity for its helpfulness to effective system quality assurance, impact analyzing of changes and software maintenance. In this paper, we propose an automatic approach called LGRTL to recover traceability links between high-level requirements and low-level design elements. This approach treats the recovery process as Bayesian classification process. Meanwhile, we add a synonym process to the preprocessing phase, and improve the Bayesian model for performing better. To evaluate the validity of the method, we perform a case study and the experimental results show that our method can enhance the effect to a certain extent.
  • Keywords
    Bayes methods; formal specification; pattern classification; software maintenance; software quality; Bayesian classification; Bayesian model; high-level requirement; learning and generating requirements traceability links; low-level design element; recovery process; requirement tracing; requirements-to-design traceability links; software maintenance; system quality assurance; Bayesian methods; Computer science; Data mining; Information retrieval; Niobium compounds; Performance evaluation; Programming profession; Quality assurance; Software maintenance; Thesauri;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5366024
  • Filename
    5366024