• DocumentCode
    2087573
  • Title

    Random Testing: Evaluation of a Law Describing the Number of Faults Found

  • Author

    Oriol, Manuel

  • Author_Institution
    Dept. of Comput. Sci., Univ. of York, York, UK
  • fYear
    2012
  • fDate
    17-21 April 2012
  • Firstpage
    201
  • Lastpage
    210
  • Abstract
    Automated random testing is an effective and predictable method for finding faults. While it was recently studied both in practice and in theory, no general laws were found that express the number of faults in function of the time or the number of tests performed. This article evaluates the Michaelis-Menten equation (Max * t)/(K + t) as a law for representing the number of faults found by automated random testing. Max is the number of faults it can uncover in the code, K is a constant dependent on the tested code and the strategy used and t is the number of tests. The evaluation relies on the testing of more than 6000 Java classes from the Qualitas Corpus.
  • Keywords
    Java; fault tolerant computing; program testing; Java class; Michaelis-Menten equation; Qualitas corpus; automated random testing; faults; law evaluation; Approximation methods; Equations; Histograms; Java; Mathematical model; Runtime; Testing; automated; random; testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Testing, Verification and Validation (ICST), 2012 IEEE Fifth International Conference on
  • Conference_Location
    Montreal, QC
  • Print_ISBN
    978-1-4577-1906-6
  • Type

    conf

  • DOI
    10.1109/ICST.2012.100
  • Filename
    6200118