• DocumentCode
    1688413
  • Title

    An Approach to Regression Test Selection of Adaptive EFSM Tests

  • Author

    Guo, Bo ; Subramaniam, Mahadevan ; Guo, Hai-Feng

  • Author_Institution
    Comput. Sci. Dept., Univ. of Nebraska-Omaha, Omaha, NE, USA
  • fYear
    2011
  • Firstpage
    217
  • Lastpage
    220
  • Abstract
    A formal approach to automatically building a regression test suite whose tests are guaranteed to exercise a given set of system changes is proposed. Given a test and a change, the approach analyzes the test description to provably predict whether or not the test will exercise the change. Adaptive tests whose descriptions involve multiple control paths and support values over commonly used data types are considered. We introduce fully-observable adaptive tests whose descriptions contain all the relevant information about their executions. A structural invariant generated from a test description identifies fully-observable tests and is used to develop a procedure to automatically select tests exercising changes.
  • Keywords
    finite state machines; regression analysis; adaptive EFSM test; extended finite state machines; fully-observable adaptive test; regression test selection; Adaptation models; Adaptive systems; Concrete; Distance measurement; Educational institutions; Impedance matching; Testing; Extended Finite State Machines; Regression Test Selection; Theorem Proving;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Theoretical Aspects of Software Engineering (TASE), 2011 Fifth International Symposium on
  • Conference_Location
    Xi´an, Shaanxi
  • Print_ISBN
    978-1-4577-1487-0
  • Type

    conf

  • DOI
    10.1109/TASE.2011.39
  • Filename
    6042082