Application of genetic algorithm in automatic software testing

Abstract

One of the major challenge and time-consuming work is optimum test data generation to assure software quality. Researchers have proposed several methods over years to generate automatically solution which have different drawbacks. In this paper, we propose Genetic Algorithm (GA) based tester with different parameters to automate the structural-oriented test data generation on the basis of internal program structure. Our proposed fitness function is intended to traverse paths of the program as more as possible. This integration improves the GA performance in search space exploration and exploitation fields with faster convergence. At last, we present some results according to our experiment which were promising in term of structural coverage and time order. © 2010 Springer-Verlag Berlin Heidelberg.