An Efficient Genetic Algorithm for Fault Based Regression Test Case Prioritization

Abstract: Software Testing is the process of validation and verification of product to provide the quality and efficiency and regression testing is the process of validating the modified software to detect errors that have been introduced into previously tested code. The test cases need to be generated as the software is modified and size of test suites will also increase. In this case, there is need of prioritization of test cases to reduce the cost of regression testing. There are number of methods for improving the efficiency in terms of time. The prioritization improves the effectiveness of regression testing by re ordering the test cases. The genetic algorithm (GA) has been proposed and implemented for prioritizing the test cases on the basis of fault coverage and execution time. The execution time and faults coverage has been given as input for test case number. The proposed algorithm has been automated and the results have been analyzed. The results representing the effectiveness of algorithm are presented with the help of GA. Total fault coverage with in time constrained environment on different examples is used for prioritization of test cases and their finite solution is obtained. Through Genetic Algorithm technique, an approach has been identified to find a suitable population, which was further formulated by GA operations to make it more flexible and efficient. The elaborations of results are shown with the help of .Net Technology. The algorithm has been automated and is analyzed for various examples.

Keywords: GA (Genetic Algorithm).