基于PSO算法的软件测试技术研究

测试数据集的全面性和覆盖完整性,对于软件测试的效果具有重要意义.该文在PSO(粒子群算法)的基础上进行了三重改进:(1)设计了具有线性特征的惯性权重系数和2个学习因子;(2)重新设计了粒子聚类密度的判别参数;(3)对PSO算法的适应度函数进行了修正.实验结果表明,用该文设计的PSO算法生成软件测试数据集合,不仅迭代收敛速度快,而且数据集的覆盖率高.

On Software Testing Technology Based on PSO Algorithm

Test data set is comprehensive and complete,and has important significance for the effect of software testing.In this paper,three improvements have been studied based on the PSO algorithm:first,design the inertia weight coefficient is linear and two learning factor;second,the redesign of the discriminant parameters of particle cluster density;and third,the fitness function of the PSO algorithm is modified.The experimental results show that the PSO algorithm is used to generate the test data set,which is not only fast,but also the high coverage rate of the data set.