• DocumentCode
    2919329
  • Title

    Formality based genetic programming

  • Author

    He, Pei ; Kang, Lishan ; Fu, Ming

  • Author_Institution
    State Key Lab. of Software Eng., Wuhan Univ., Wuhan
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    4080
  • Lastpage
    4087
  • Abstract
    Genetic programming (GP) is an illogical method for automatic programming. It shows creativity in discovering a desired program to solve problem, but in essence bases its searching principle on software testing. This paper is dedicated to establishing a novel GP which combines classical GP and formal approaches like Hoarepsilas logic, model checking, and automaton, etc. The result indicates these methods can collaborate in the framework pretty well. As has been demonstrated by the experiment, they work in a way that preserves their advantages while each compensates for the deficiencies of the other. So, once an approximate program is obtained, we can say with certainty it is correct with respect to its corresponding pre- and post-conditions.
  • Keywords
    genetic algorithms; program testing; program verification; approximate program; automatic programming; formality based genetic programming; software testing; Evolutionary computation; Genetic programming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4631354
  • Filename
    4631354