Optimizing test case generation in glass box testing using Bio-inspired Algorithms

Abstract

Software testing is performed with the major intent of detecting errors and bugs in the software. It helps to analyze the stability, reliability and quality of the software which can be accomplished by suitable number of test data. In this paper, we propose an approach for automated test case generation process that aids in the generation of the test cases, using a control flow graph. We specifically focus on three Bio-inspired approaches viz. Genetic algorithm, Firefly Algorithm and the Bacterial Foraging algorithm techniques. We use these approaches for automatic generation of test data and then code coverage is done with these generated test data. Results carried out with these generated test data show that the Firefly algorithm and Bacterial foraging algorithm are effective in achieving better coverage of code over Genetic algorithm.