6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

Supporting evidence-based Software Engineering with collaborative information retrieval

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2010.9,
        author={Heri Ramampiaro and Daniela Cruzes and Reidar Conradi and Manoel Mendona},
        title={Supporting evidence-based Software Engineering with collaborative information retrieval},
        proceedings={6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2011},
        month={5},
        keywords={Collaborative Information Retrieval Empirical Software Engineering Systematic Review},
        doi={10.4108/icst.collaboratecom.2010.9}
    }
    
  • Heri Ramampiaro
    Daniela Cruzes
    Reidar Conradi
    Manoel Mendona
    Year: 2011
    Supporting evidence-based Software Engineering with collaborative information retrieval
    COLLABORATECOM
    ICST
    DOI: 10.4108/icst.collaboratecom.2010.9
Heri Ramampiaro1,*, Daniela Cruzes1,*, Reidar Conradi1,*, Manoel Mendona2,*
  • 1: Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), Norway
  • 2: Department of Computer Science/UFBA, Salvador, BA - Brazil
*Contact email: heri@idi.ntnu.no, dcruzes@idi.ntnu.no, conradi@idi.ntnu.no, manoel.g.mendonca@gmail.com

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.