• DocumentCode
    2228917
  • Title

    MUGAMMA: Mutation Analysis of Deployed Software to Increase Confidence and Assist Evolution

  • Author

    Kim, Sang-Woon ; Harrold, Mary Jean ; Kwon, Yong-Rae

  • Author_Institution
    Dept. of EECS, KAIST, Daejeon
  • fYear
    2006
  • fDate
    7-10 Nov. 2006
  • Firstpage
    10
  • Lastpage
    10
  • Abstract
    This paper presents a novel approach to unit testing that lets users of deployed software assist in performing mutation testing of the software. Our technique, MUGAMMA, provisions a software system so that when it executes in the field, it will determine whether users´ executions would have killed mutants (without actually executing the mutants), and if so, captures the state information about those executions. In the absence of bug reports, knowledge of executions that would have killed mutants provides additional confidence in the system over that gained by the testing performed before deployment. Captured information about the state before and after execution of units (e.g., methods) can be used to construct test cases for use in unit testing when changes are made to the software. The paper also describes our prototype MuGamma implementation along with a case study that demonstrates its potential efficacy.
  • Keywords
    program debugging; program testing; MUGAMMA; bugs; deployed software; mutation analysis; unit testing; Automatic testing; Environmental economics; Genetic mutations; Monitoring; Performance analysis; Performance evaluation; Software performance; Software quality; Software testing; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mutation Analysis, 2006. Second Workshop on
  • Conference_Location
    Raleigh, NC
  • Print_ISBN
    0-7695-2897-X
  • Type

    conf

  • DOI
    10.1109/MUTATION.2006.8
  • Filename
    4144729