一种改进的遗传算法在测试用例中的应用研究

Applied Research on An Improved Genetic Algorithm Used in Optimizing Test Cases for Automatic Generation

测试用例的自动生成是软件测试的重要环节,其关键问题是路径搜索问题,遗传算法作为一种高效的搜索寻优算法被广泛应用到测试用例中。该文提出一种改进的遗传算法,对选择算子和交叉算子进行改进,把传统遗传算法和最优保存策略相结合,提高遗传算法的局部搜索能力。研究表明,该算法比传统遗传算法在生成测试用例的效率方面更具优势。

Test data generation is one of the major task in the software testing process, the key problem is the path search problem,as an effective search algorithm, genetic algorithm has been widely used for test date generation. This paper proposes a modified genetic algorithm, improves the select and crossover operator of genetic algorithm against the shortcomings of premature convergence, and combines the improved selection operator and the optimal preservation strategy for improving search capabilities in the local space and the overall operating efficiency. Experimental result shows that the new algorithm has obvious advantages compared with traditional genetic algorithm.