• DocumentCode
    3696819
  • Title

    DRS: A Developer Risk Metric for Better Predicting Software Fault-Proneness

  • Author

    Shou-Yu Lee;Yihao Li

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Texas at Dallas, Richardson, TX, USA
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    120
  • Lastpage
    127
  • Abstract
    Previous studies have reported that the performance of a developer can greatly impact the quality of the software he/she has worked on. Such performance can be measured using two developer risk metrics during a particular development period. One is the ratio of the number of bug-introduce commits to the total number of commits made by a developer (i.e., the DQ metric). The other is the proportion of faulty software modules out of all modules modified by the developer (i.e., the BR metric). However, all bug-introduce commits, no matter its severity, are treated equally by both DQ and BR metrics. Moreover, the complexity of a software module that a developer is working on may also have a potential impact on his/her performance but is not considered by either DQ or BR. To resolve these two problems, we propose Developer Risk Score (DRS), which takes both program complexity and the severity of bug-introduce commits into account, to evaluate the performance of a developer. Nine software risk metrics based on DRS are further derived to predict the fault proneness of a given software module. Results from our case studies show that (1) DRS-based software risk metrics are generally more correlated with the number of bugs in a software module and the cumulative severity score of bug-introduce commits for a module than DQ-and BR-based metrics, and (2) models using DRS-based metrics are generally more effective in predicting software fault-proneness than those using DQ-and BR-based metrics.
  • Keywords
    "Measurement","Software","Complexity theory","Predictive models","Computer bugs","Correlation","Java"
  • Publisher
    ieee
  • Conference_Titel
    Trustworthy Systems and Their Applications (TSA), 2015 Second International Conference on
  • Type

    conf

  • DOI
    10.1109/TSA.2015.27
  • Filename
    7335952