Title :
Software test cases generation based on improved particle swarm optimization
Author :
Ming Huang ; Chunlei Zhang ; Xu Liang
Author_Institution :
Software Technol. Inst., Dalian Jiaotong Univ., Dalian, China
Abstract :
The analysis of test case generation based on particle swarm algorithm introduced the group self-activity feedback (SAF) operator and Gauss mutation (G) changing inertia weight to improve the performance of particle swarm optimization (PSO). Using the improved algorithm in software test case, experiments show that the introduction of a single path fitness function structure and multi-path fitness calculation of parallel thinking are superior to the iteration time in single path test than standard PSO, and more efficient in multi-path test case generation.
Keywords :
automatic test pattern generation; particle swarm optimisation; program testing; Gauss mutation changing inertia weight; group SAF operator; improved PSO algorithm; multipath fitness calculation; particle swarm optimization; self-activity feedback; single path fitness function structure; software test case generation; Algorithm design and analysis; Genetic algorithms; Particle swarm optimization; Sociology; Software; Software algorithms; Statistics; Gauss Mutation; Particle Swarm optimization; Self-active Feedback; Test Case;
Conference_Titel :
Information Technology and Electronic Commerce (ICITEC), 2014 2nd International Conference on
Print_ISBN :
978-1-4799-5298-4
DOI :
10.1109/ICITEC.2014.7105570
