• DocumentCode
    257582
  • Title

    Supporting traceability through affinity mining

  • Author

    Gervasi, Vincenzo ; Zowghi, Didar

  • Author_Institution
    Dipt. di Inf., Univ. di Pisa, Pisa, Italy
  • fYear
    2014
  • fDate
    25-29 Aug. 2014
  • Firstpage
    143
  • Lastpage
    152
  • Abstract
    Traceability among requirements artifacts (and beyond, in certain cases all the way to actual implementation) has long been identified as a critical challenge in industrial practice. Manually establishing and maintaining such traces is a high-skill, labour-intensive job. It is often the case that the ideal person for the job also has other, highly critical tasks to take care of, so offering semi-automated support for the management of traces is an effective way of improving the efficiency of the whole development process. In this paper, we present a technique to exploit the information contained in previously defined traces, in order to facilitate the creation and ongoing maintenance of traces, as the requirements evolve. A case study on a reference dataset is employed to measure the effectiveness of the technique, compared to other proposals from the literature.
  • Keywords
    data mining; software maintenance; systems analysis; affinity mining; critical tasks; industrial practice; labour-intensive job; reference dataset; requirements artifacts; semiautomated support; trace establishment; trace maintainance; trace management; traceability support; Context; Joining processes; Maintenance engineering; Pragmatics; Proposals; Semantics; Software;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Requirements Engineering Conference (RE), 2014 IEEE 22nd International
  • Conference_Location
    Karlskrona
  • Print_ISBN
    978-1-4799-3031-9
  • Type

    conf

  • DOI
    10.1109/RE.2014.6912256
  • Filename
    6912256