基于遗传算法的类对象测试数据自动生成研究

Investigation of automatic generation of class-object test data based on genetic algorithm

在测试数据自动化生成方法中,对类对象测试数据的生成目前在实际中还没有完善的解决方法。针对这个不足,研究了基于遗传算法的类对象测试数据自动生成技术。在扩展海明距离法的基础上,提出了一种在遗传算法中生成类对象测试数据的适应度函数改进方法,并在理论上证明了该方法在缩短执行时间上的可行性。最后将方法实验于实际系统,实验结果显示在生成类对象测试数据的效率和准确性上都有明显的提高。

In the automatic generation of test data, there is no sound solution to generating class-object test data in the practical applications. To overcome this shortcoming, automatic generation of class-object test data on Genetic Algorithm （GA） was investigated. On the basis of Extended Hamming Distance （EHD）, a modified method was proposed for fitness function of generating class-object test data by using GA, and the feasibility of reducing the execution time was proved in theory. At last the method was applied to real system. The testing results show that the method signitlcanfly improves the efficiency and accuracy of generating class-object test data.