• DocumentCode
    2797056
  • Title

    Combining Single-Version and Evolutionary Dependencies for Software-Change Prediction

  • Author

    Kagdi, Huzefa ; Maletic, Jonathan I.

  • Author_Institution
    Kent State Univ., Kent
  • fYear
    2007
  • fDate
    20-26 May 2007
  • Firstpage
    17
  • Lastpage
    17
  • Abstract
    The paper advocates the need for the investigation and development of a software-change prediction methodology that combines the change sets estimated from software dependency analysis (via single-version analysis) and the actual change sets found in software version histories (via multiple-version analysis). Traditionally prescribed methodologies such as Impact Analysis (IA) are based on the former, whereas a more recent methodology, mining software repository (MSR), is based on the latter. The research hypothesis is that combining these two methodologies will result in an overall improved support for software-change prediction.
  • Keywords
    configuration management; data mining; data warehouses; management of change; software development management; MSR method; change sets; evolutionary dependencies; mining software repository; multiple-version analysis; single-version analysis; software dependency analysis; software version histories; software-change prediction; Collaborative software; Computational efficiency; Computer science; History; Open source software; Performance analysis; Software performance; Software systems; State estimation; Unified modeling language;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mining Software Repositories, 2007. ICSE Workshops MSR '07. Fourth International Workshop on
  • Conference_Location
    Minneapolis, MN
  • Print_ISBN
    0-7695-2950-X
  • Type

    conf

  • DOI
    10.1109/MSR.2007.2
  • Filename
    4228654