• Journal of Software Engineering Society
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• v.24 no.2
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• pp.35-45
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• 2011

Simulated annealing has been studied a long times. And it is one of the effective techniques for test data generation. But basic SA methods showed bad performance because of neighborhood selection strategies in the case of large input domain. To overcome this limitation, we propose new neighborhood selection approach, Branch Distance. We performs case studies based on the proposed approach to evaluate it's performance and to compare it whit basic SA and Random test generation. The results of the case studies appear that proposed approach show better performance than the other approach.