Combined Genetic and simulated annealing approach for test case prioritization

Abstract

Background: The test case prioritization of regression Testing is described. Methods: A new test case prioritization algorithm is proposed to get better the rate of fault detection and cost reduction. Heuristic Techniques like Genetic Algorithm (GA) and Simulated Annealing (SA) are employed. It prioritizes the test cases depends on fault detection ability and execution time taken. Findings: The implementation of proposed algorithm in JAVA is found to produce optimal or near optimal results. The efficiency of proposed regression testing technique is proved by comparing it with GA and SA methods individually. Applications: A complete automation tool for the complete usage of the algorithm is being developed. It will also be analyzed on larger projects with large number of test cases and faults.