Cost cognizant history based prioritization of test case for regression testing using immune algorithm

Abstract

Regression testing is one among the strongest testing criteria which ensure the quality of the software under test. However, regression testing is too expensive due to execution of too many test cases. Test case prioritization is one of the traditional techniques which improve the regression testing by proposing a test case order that increases the rate of fault detection. In this paper, we propose a cost - cognizant history based test case prioritization approach that utilizes the historical information of the test cases like cost, fault identified by the test case and the severity of the identified fault for prioritization. Also an artificial immune system based, Clonal selection algorithm is proposed to find an effective test case order from existing test suite. To evaluate the proposed approach, controlled experiment were performed and the evaluation results indicates the test case order produced by proposed approach shows improvement in terms of average percentage of fault detected per cost.