• DocumentCode
    3612515
  • Title

    Analysis of task effort estimation accuracy based on use case point size

  • Author

    Popovic, Jovan ; Bojic, Dragan ; Korolija, Nenad

  • Author_Institution
    Microsoft Dev. Center Serbia, Microsoft Corp., Belgrade, Serbia
  • Volume
    9
  • Issue
    6
  • fYear
    2015
  • Firstpage
    166
  • Lastpage
    173
  • Abstract
    The use case point (UCP) method is one of the most commonly used size estimation methods in software development. Applicability of UCP size for the project effort estimation is thoroughly investigated; however, little attention is devoted to the effort estimation of particular task types. The authors have created and cross-compared prediction models for estimating task-type efforts by means of UCP size using an Online analytical processing model and R packages on a set of 32 real-world projects, with the goal of facilitating analysis of the correlation between project sizes and effort required to complete task types. Requirements, scoping, functional specification, and functional testing task types have up to two times better estimation accuracies than project effort. Implementation has slightly better accuracy than the project effort, while the other task types are not correlated to the UCP size. Using estimates of the most correlated task types and other techniques, such as expert judgment for others, we improved the overall project effort prediction accuracy and decreased the error from 26 to 16%.
  • Keywords
    data mining; formal specification; project management; software development management; software packages; task analysis; R package; UCP method; complete task type; correlated task type; cross-compared prediction model; functional specification; functional testing task type; online analytical processing model; project effort estimation; requirement analysis; scoping analysis; software development; task type effort estimation accuracy analysis; use case point size; used size estimation method;
  • fLanguage
    English
  • Journal_Title
    Software, IET
  • Publisher
    iet
  • ISSN
    1751-8806
  • Type

    jour

  • DOI
    10.1049/iet-sen.2014.0254
  • Filename
    7360957