Survey Paper on Optimum Selection of Ga Algorithm's Parameters for Software Test Data Generation

Sonam Kamboj, Mohinder Singh

Abstract: This paper empirically evaluates four metaheuristic search techniques namely Genetic Algorithm; artificial bee colony and Bing Bang Big Crunch Algorithm for automatic test data generation for procedure oriented programs using structural symbolic testing method. Test data is generated for each feasible path of the programs. All the four algorithms have been evaluated on average percentage coverage per path.

Keywords: Automatic test data generation, Artificial Bee Colony ABC Algorithm, Symbolic testing, Soft computing, Search Algorithm

How to Cite?: Sonam Kamboj, Mohinder Singh, "Survey Paper on Optimum Selection of Ga Algorithm's Parameters for Software Test Data Generation", Volume 3 Issue 6, June 2014, International Journal of Science and Research (IJSR), Pages: 46-49, https://www.ijsr.net/getabstract.php?paperid=1061404, DOI: https://dx.doi.org/10.21275/1061404