Scalability of the coevolutionary automated software correction system

Authors:
Josh L. Wilkerson;Daniel R. Tauritz
Affiliations:
Missouri University of Science and Technology, Rolla, MO, USA;Missouri University of Science and Technology, Rolla, MO, USA
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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Coevolutionary automated software correction

Proceedings of the 12th annual conference on Genetic and evolutionary computation

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Abstract

The Coevolutionary Automated Software Correction system addresses in an integral and fully automated manner the complete cycle of software artifact testing, error location, and correction phases. It employs a coevolutionary approach where software artifacts and test cases are evolved in tandem. The test cases evolve to better find flaws in the software artifacts and the software artifacts evolve to better behave to specification when exposed to the test cases, thus causing an evolutionary arms race. Experimental results are presented which demonstrate the scalability of the Coevolutionary Automated Software Correction system by establishing correlations between program size and both success rate and estimated convergence rate that are at most linear.