• DocumentCode
    2024269
  • Title

    Evaluating software project prediction systems

  • Author

    Shepperd, Martin

  • Author_Institution
    Sch. of IS, Comput. & Maths, Brunei Univ., Manchester
  • fYear
    2005
  • fDate
    1-1 Sept. 2005
  • Lastpage
    2
  • Abstract
    The problem of developing usable software project cost prediction systems is perennial and there are many competing approaches. Consequently, in recent years there have been exhortations to conduct empirically based evaluations in order that our understanding of project prediction might be based upon real world evidence. We now find ourselves in the interesting position of possessing this evidence in abundance. For example, a review of just three software engineering journals identified 50 separate studies and overall several hundred studies have been published. This naturally leads to the next step of needing to construct a body of knowledge, particularly when not all evidence is consistent. This process of forming a body of knowledge is generally referred to as metaanalysis. It is an essential activity if we are to have any hope of making sense of, and utilising, results from our empirical studies. However, it becomes apparent that when systematically combining results many difficulties are encountered
  • Keywords
    software cost estimation; software management; metaanalysis; software engineering; software project cost prediction systems; Computer industry; Costs; Learning systems; Machine learning; Parametric statistics; Predictive models; Software engineering; Software metrics; Software systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Metrics, 2005. 11th IEEE International Symposium
  • Conference_Location
    Como
  • ISSN
    1530-1435
  • Print_ISBN
    0-7695-2371-4
  • Type

    conf

  • DOI
    10.1109/METRICS.2005.22
  • Filename
    1509280