• DocumentCode
    2745567
  • Title

    Predicting Faults from Cached History

  • Author

    Kim, Sunghun ; Zimmermann, Thomas ; Whitehead, E. James ; Zeller, Andreas

  • Author_Institution
    Massachusetts Inst. of Technol., Cambridge, MA
  • fYear
    2007
  • fDate
    20-26 May 2007
  • Firstpage
    489
  • Lastpage
    498
  • Abstract
    We analyze the version history of 7 software systems to predict the most fault prone entities and files. The basic assumption is that faults do not occur in isolation, but rather in bursts of several related faults. Therefore, we cache locations that are likely to have faults: starting from the location of a known (fixed) fault, we cache the location itself, any locations changed together with the fault, recently added locations, and recently changed locations. By consulting the cache at the moment a fault is fixed, a developer can detect likely fault-prone locations. This is useful for prioritizing verification and validation resources on the most fault prone files or entities. In our evaluation of seven open source projects with more than 200,000 revisions, the cache selects 10% of the source code files; these files account for 73%-95% of faults - a significant advance beyond the state of the art.
  • Keywords
    cache storage; software fault tolerance; 7 software system version history; cache history; fault-prone location prediction; resource validation; resource verification; Fault detection; Fault diagnosis; History; Isolation technology; Open source software; Prediction algorithms; Software algorithms; Software quality; Software systems; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, 2007. ICSE 2007. 29th International Conference on
  • Conference_Location
    Minneapolis, MN
  • ISSN
    0270-5257
  • Print_ISBN
    0-7695-2828-7
  • Type

    conf

  • DOI
    10.1109/ICSE.2007.66
  • Filename
    4222610