• DocumentCode
    2378907
  • Title

    Ant Colony Optimization directed program abstraction for software bounded model checking

  • Author

    Cheng, Xueqi ; Hsiao, Michael S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Virginia Tech, Blacksburg, VA
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    46
  • Lastpage
    51
  • Abstract
    The increasing complexity and size of software designs has made scalability a major bottleneck in software verification. Program abstraction has shown potential in alleviating this problem through selective search space reduction. In this paper, we propose an Ant Colony Optimization (ACO)-directed program structure construction to formulate a novel under-approximation based program abstraction (UAPA). By taking advantage of the resulting abstraction, a new software bounded model checking framework is built with the aim of improving the performance of property checking, especially for property falsification. Experimental results on various programs showed that the proposed ACO-directed program abstraction can dramatically improve the performance of software bounded model checking with significant speedups.
  • Keywords
    approximation theory; optimisation; program verification; search problems; ant colony optimization; property falsification; selective search space reduction; software bounded model checking; under-approximation based program abstraction; Ant colony optimization; Concrete; Context modeling; Explosions; Hardware; Power system modeling; Scalability; Software performance; Space exploration; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Design, 2008. ICCD 2008. IEEE International Conference on
  • Conference_Location
    Lake Tahoe, CA
  • ISSN
    1063-6404
  • Print_ISBN
    978-1-4244-2657-7
  • Electronic_ISBN
    1063-6404
  • Type

    conf

  • DOI
    10.1109/ICCD.2008.4751839
  • Filename
    4751839