• DocumentCode
    2333337
  • Title

    Estimating software maintenance effort from use cases: An industrial case study

  • Author

    Ku, Yan ; Du, Jing ; Yang, Ye ; Wang, Qing

  • Author_Institution
    Lab. for Internet Software Technol., Inst. of Software, Beijing, China
  • fYear
    2011
  • fDate
    25-30 Sept. 2011
  • Firstpage
    482
  • Lastpage
    491
  • Abstract
    Software maintenance effort constitutes a major portion of the software lifecycle effort. Its estimation is vital for successful project planning and strategic resource allocation. In this paper, we conduct and report an industrial case study in this field. The data set was collected from an industrial software process management tool QONE (formerly SoftPM). The methodology proposed provides corresponding guidance for effort estimation in software evolutionary projects that employ use-cases in capturing maintenance requirements. And the model, constructed using the linear regression analysis and validated by the leave-one-out cross-validation, provides an effort prediction for the future maintenance of the project. The analysis results indicate that the methodology can be applied at an early stage of the project life cycle and provides a good tradeoff among simplicity, early-estimating and accuracy in one estimate.
  • Keywords
    regression analysis; software maintenance; software management; QONE; SoftPM; industrial software process management tool; leave-one-out cross-validation; linear regression analysis; software evolutionary project; software lifecycle; software maintenance effort estimation; Accuracy; Data models; Estimation; Maintenance engineering; Predictive models; Software; Unified modeling language; effort estimation; estimate model; requirement elaboration; software maintenance; use case;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Maintenance (ICSM), 2011 27th IEEE International Conference on
  • Conference_Location
    Williamsburg, VI
  • ISSN
    1063-6773
  • Print_ISBN
    978-1-4577-0663-9
  • Electronic_ISBN
    1063-6773
  • Type

    conf

  • DOI
    10.1109/ICSM.2011.6080815
  • Filename
    6080815