• DocumentCode
    147935
  • Title

    Techniques for Automatic Detection of Metamorphic Relations

  • Author

    Kanewala, Upulee

  • Author_Institution
    Comput. Sci. Dept., Colorado State Univ., Fort Collins, CO, USA
  • fYear
    2014
  • fDate
    March 31 2014-April 4 2014
  • Firstpage
    237
  • Lastpage
    238
  • Abstract
    Much software lacks test oracles, which limits automated testing. Metamorphic testing is one proposed method for automating the testing process for programs without test oracles. Unfortunately, finding appropriate metamorphic relations for use in metamorphic testing remains a labor intensive task, which is generally performed by a domain expert or a programmer. We are investigating novel approaches for automatically predicting metamorphic relations using machine learning techniques. Preliminary results show that the proposed techniques are highly effective in predicting metamorphic relations.
  • Keywords
    automatic testing; learning (artificial intelligence); program testing; automated software testing; automatic metamorphic relation detection techniques; machine learning techniques; metamorphic testing; Accuracy; Feature extraction; Kernel; Predictive models; Support vector machines; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Testing, Verification and Validation Workshops (ICSTW), 2014 IEEE Seventh International Conference on
  • Conference_Location
    Cleveland, OH
  • Type

    conf

  • DOI
    10.1109/ICSTW.2014.62
  • Filename
    6825666