TEST SUITE OPTIMIZATION USING NATURE BASED METAHEURISTIC APPROACH

Abstract

Regression testing is a type of software testing that intends to validate modified software and it confirms that modifications made to the software have no adverse side effects. The goal of regression testing is to validate the modified software. Due to the resource and time constraints, it becomes necessary to develop techniques to minimize existing test suites by eliminating redundant test cases and prioritizing them. Running all test cases in an existing test suite can consume an inordinate amount of time and resources. Thus, it is necessary to select the minimum set of test cases from existing test suite with the ability to cover all the faults in minimum execution time. When analyzing large test suits, redundancies are identified in test cases, hence, it is necessary to reduce these suites, in order to fit the available resources, without severely compromising the coverage of the test adequacy criterion being observed. Test case prioritization techniques intend to arrange test cases of a test suite in a way, with the goal of maximizing some objective function. There are various classical techniques of test case prioritization. In this research we proposed a nature inspired meta-heuristic approach for test prioritization.