Title :
Automatic generation of software test data based on hybrid particle swarm genetic algorithm
Author :
Ding, Rui ; Feng, Xianbin ; Li, Shuping ; Dong, Hongbin
Author_Institution :
Comput. Dept., Mudanjiang Normal Univ., Mudanjiang, China
Abstract :
A hybrid particle swarm genetic algorithm is purposed to apply in software testing using case automated generations. On the basis of classical genetic algorithm, the algorithm divided the population into “families”, influencing the convergence efficiency by crossover in family, keeping the diversity of the population by crossover between families; meanwhile, enhancing the speed of convergence by the PSO crossover (commixed the thought of PSO in genetic algorithm) According to the characteristics of software testing problems, we designed the corresponding fitness function and the encoding method. The results of data experiment were given to illustrate the effectiveness of the algorithm.
Keywords :
encoding; genetic algorithms; particle swarm optimisation; program testing; PSO crossover; convergence efficiency; encoding method; fitness function; hybrid particle swarm genetic algorithm; population diversity; software test data automatic generation; Genetics; Reliability; Case Automatically Generates; Genetic Algorithm; Particle Swarm Optimization; Software Testing;
Conference_Titel :
Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-2363-5
DOI :
10.1109/EEESym.2012.6258748