基于改进的自适应遗传算法HCGA的测试数据自动生成

Automated Test Data Generation Based on Improved Adaptive Genetic Algorithm HCGA

  • 摘要: 针对软件测试数据的自动生成,提出了一种自适应遗传算法和爬山算法相结合的改进算法HCGA.通过设计自适应交叉和变异算子,加强了遗传算法的前期全局搜索能力;在进化后期嵌入了爬山算法,提高了局部搜索能力.实验结果表明,该算法在测试数据的自动生成上优于遗传算法,提高了效率.

     

    Abstract: An improved algorithm HCGA is proposed here based on the combination of adaptive genetic algorithm and hill climbing method for automated software test data generation.Adaptive crossover operator and mutation operator are designed to enhance the global search capability of genetic algorithm at starting.Afterwards hill climbing method is embedded to enhance the local search capability.Test examples show that it is better than genetic algorithm and can improve the efficiency of automated test data generation.

     

/

返回文章
返回
Baidu
map