• DocumentCode
    694310
  • Title

    An application of learning effects for assessing work performance using a software reliability growth model with multiple change-points

  • Author

    Kuei-Chen Chiu ; Shulan Hsieh

  • Author_Institution
    Inst. of Allied Health Sci., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    1711
  • Lastpage
    1715
  • Abstract
    Learning effects exist with regard to various behaviors, and especially work-related processes. This study measures the performance of a software testing project with time-varying effects using a software reliability growth model (SRGM), and discusses the changes in learning effects parameters with change-points in the model. We employ Chiu´s [2] model to construct the time-varying learning effects and measure the performance of the software testing project using the data set in Huang and Hung [10]. This paper also discusses the time-lag between error-detected and error-removed that exists with different learning concepts. The results indicate that error-removed requires more cognitive learning process time, and this information can be used to help project managers mastering the staff and the process of software testing, efficiently.
  • Keywords
    learning (artificial intelligence); program testing; software reliability; SRGM; cognitive learning process time; error detection; error removal; software reliability growth model; software testing project performance measures; time-varying effects; time-varying learning effects; work performance assessment; work-related processes; Analytical models; Data models; Fitting; Predictive models; Software; Software reliability; Software testing; Change-points; Non-Homogeneous Poisson Process (NHPP); Software reliability; Time-varying Learning Effects; behavior learning effects; cognitive learning effects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Engineering and Engineering Management (IEEM), 2013 IEEE International Conference on
  • Conference_Location
    Bangkok
  • Type

    conf

  • DOI
    10.1109/IEEM.2013.6962702
  • Filename
    6962702