A Hybrid Bat Approach With Tabu Search Algorithm For Test Case Selection In Object Oriented Testing

All research made on the Object-Oriented (OO) paradigms focus on the fundamentals of analysis, programming, and design. The primary problem found in testing the systems which are object-oriented is a methodology of standard testing and this may not be very useful. The test case may execute software using a new set consisting of some input values and will then compare them to the output to check if the test has passed. An optimum test case set is obtained using a process of selection that is viewed to be a problem of optimization. Thus, metaheuristic optimizing or searching is a technique used often for optimizing or searching which is used in automated testing of software. The BAT Algorithm is a metaheuristic that is dependent on the property of echolocation of the miniaturized scale bats. The property further controls the conduct of search of the bats of a small-scale and making them discover prey thus enabling them to identify distinctive types of bugs irrespective of the fact they are found to be dull. The work also proposed a new and hybrid Tabu search algorithm using the BAT for the selection of test case.