• DocumentCode
    545568
  • Title

    Supporting evidence-based Software Engineering with collaborative information retrieval

  • Author

    Ramampiaro, Heri ; Cruzes, Daniela ; Conradi, Reidar ; Mendona, Manoel

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Norwegian Univ. of Sci. & Technol. (NTNU), Trondheim, Norway
  • fYear
    2010
  • fDate
    9-12 Oct. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The number of scientific publications is constantly increasing, and the results published on Empirical Software Engineering are growing even faster. Some software engineering publishers have began to collaborate with research groups to make available repositories of software engineering empirical data. However, these initiatives are limited due to issues related to the available search tools. As a result, many researchers in the area have adopted a semi-automated approach for performing searches for systematic reviews as a mean to extract empirical evidence from published material. This makes this activity labor intensive and error prone. In this paper, we argue that the use of techniques from information retrieval, as well as text mining, can support systematic reviews and improve the creation of repositories of SE empirical evidence.
  • Keywords
    information retrieval; publishing; reviews; software engineering; collaborative information retrieval; evidence based software engineering; scientific publications; software engineering publishers; systematic review; text mining; Data mining; Information retrieval; Systematics; Collaborative Information Retrieval; Empirical Software Engineering; Systematic Review;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2010 6th International Conference on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-963-9995-24-6
  • Type

    conf

  • Filename
    5767051