Improved Meta-Heuristic Technique for Test Case Prioritization

Abstract

Time is a very critical factor for decision of cost of any software. The cost and validity of software is based on the quality and quantity of the existing test cases. A large number of software testing approaches are available having both advantages and limitations. Original test cases are supposed to be reused and the new test cases have to be supplemented in regression testing of the updated software. For effective and efficient test case prioritization, the techniques like test case prioritization and test case selection were introduced for scheduling test cases and implementing test cases for fulfillment of some particular criteria. Test case prioritization supports the most useful test cases to execute first by making software testing cost-effective and efficiently covering most extreme number of faults in least time. But test case prioritization requires huge time and effort. This paper has proposed an improved meta-heuristic technique (Ant Colony Optimization) algorithm to find the best optimal path by prioritization of test cases.