Use of Optimized Genetic Algorithm for Software Testing

The development of any software product involves various phases. Software testing is one of them. There are multiple testing methods associated to make the product free from error and provide the complete flawless functional capabilities. Software Engineering includes the testing of any such product for making it feasible to the end users by removing all such bugs. Artificial Intelligence can be embedded with the testing phase of Software Engineering to speed up the process and generate better results by applying various test cases. The use of an optimized genetic algorithm from Artificial Intelligence can help us to improve the test cases. The test cases can be enhanced by learning for its own. That is the actual concept of Artificial Intelligence. This paper demonstrates an algorithm which can be applied to both black box and white box testing to get some of the best test cases rather than selecting all the parts.