Abstract—Software evaluation has a crucial role in the life cycle of software production system. Producing suitable data for testing the behavior of the software is a subject of many researches in software engineering. In this paper software quality control with criteria of covering application paths is considered and a new method based on genetic algorithm for generating optimal test data is proposed. In this algorithm, the fitness function, population production mechanism and other parameters of genetic algorithm is determined. In addition, the population production stopping criteria is based on critical edges of control flow graph. Critical edges are those that their presence in a control flow graph path represents the presence of other edges and the edges test shows the adequacy of graph test paths. The simulation results on prototype test data show the effectiveness of the proposed method.
Index Terms—Software engineering, genetic algorithm, path covering, data.
S. Keshavarz is with the Computer Engineering Department at Islamic Azad University, Arak branch, Arak, Iran (Corresponding author, e-mail: email@example.com).
R. Javidan is with Department of Computer Engineering and Information Technology, Shiraz University of Technology, Shiraz, Iran (e-mail: firstname.lastname@example.org).
Cite: S. Keshavarz and Reza Javidan, "Software Quality Control Based on Genetic Algorithm," International Journal of Computer Theory and Engineering vol. 3, no. 4, pp. 579-584, 2011.