Multi-objective optimization for object-oriented testing using stage-based genetic algorithm

Abstract

A multi-objective optimization involves optimizing a number of objectives simultaneously. The Multi-Objective Optimization Problem has a set of solutions, each of which satisfies the objectives at an acceptable level. An optimization algorithm named SBGA (stage-based genetic algorithm), with new GA operators is attempted. The multiple objectives considered for optimization are maximum path coverage with minimum execution time and test-suite minimization. The coverage and the no. of test cases generated using SBGA are experimented with simple object-oriented programs. The data flow testing of OOPs in terms of path coverage are resulted with almost 88%. Thus, the efficiency of generated testcases has been improved in terms of path coverage with minimum execution time. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.