一种基于改进遗传算法的测试用例自动生成研究

测试用例的生成是软件测试领域的关键技术问题。近年来,受生物进化思想启发得出的一种全局优化算法的遗传算法用于测试用例的自动生成方向的研究,对于软件测试的自动化有着重要的影响。为了生成高效的测试用例,笔者提出了一种改进的遗传算法,该算法采用实数编码方式,采用逻辑覆盖原则,将遗传算法的适应度函数进行改进并加入遗传导向控制,这样有利于种群的多样性遗传,避免种群早熟收敛现象,并结合Delaunay三角网生成程序进行说明,验证了该算法的有效性。

Test Case Generation Based on an Improved Genetic Algorithm

Test case generation is the key technology in the field of software testing. In recent years, according to evolutionary thinking, we get a global optimization algorithm called genetic algorithm, the algorithm has been used for the automatic generation of test cases and it is very important for the automation of software testing. In order to generate high quality test cases, this paper proposes an improved genetic algorithm. The algorithm adopts real number coding and the principles of logic cover, while the fitness function to be improved. In addition, it adds genetic-oriented control. The algorithm is conducive to population diversity and avoids premature convergence phenomenon, and it is described by using Delaunay triangulation generated program. Finally, the example demonstrates the effectiveness of the improved genetic algorithm.