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
Link To Document :
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