产生多条路径上测试用例的改进遗传算法

Improved Genetic Algorithm for Multiple Path Coverage Test Data Generation

测试用例的产生是软件测试过程中的重要环节,也是瓶颈之一。遗传算法作为一种高效的搜索寻优算法,近年来较多地用于自动化测试中产生测试用例。该文结合数据库管理系统源代码的特点,在基本遗传算法的基础上,结合“位权重”和“邻居影响”的思想,提出了用于产生多条路径上测试用例的改进遗传算法,并通过实验验证了该算法的有效性。

Test data generation is one of the major task within the software testing process as well as a bottleneck. As an effective search algorithm, genetic algorithm has been used for test data generation in many automatic testing processes recently. Considering the characteristics of DBMS source code and the genetic algorithm, this paper proposes an improved genetic algorithm for multiple test data generation for multiple path coverage, based on bit weight and neighborhood influence. Experimental results show that this algorithm is effective.