A Software Test Case Automatic Generation Technology Based on the Modified Particle Swarm Optimization Algorithm
Zhenzhen Wang, Qiaolian Liu · 2018
As the software project has been more and more complex than ever, software test case automatic generation is of great importance for software testing. In this paper, we aim to propose a novel software test case automatic generation technology to promote the quality of software testing. The main innovation of this paper lies in that we introduce the PSO algorithm to generate software case. Particularly, in order to enhance the performance of PSO, we propose an improved PSO algorithm, in which the position and velocity of each particle represented as vectors in the multiple dimensional binary solution space. Afterwards, a novel software test case automatic generation algorithm based on PSO is proposed. Experimental results demonstrate that the proposed algorithm is able to obtain both high performance and lower time cost in software test case automatic generation.