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
Link To Document :
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