Efficient Reduction of Model-Based Generated Test Suites through Test Case Pair Prioritization
During the development and maintenance of software, test suites often reach a size that exceeds the costs allocated for test suite execution. In such a case, the test suite needs to be reduced. Many papers are dedicated to the problem of test suite reduction. Most of them consider the removal or merging of test cases. However, less attention has been paid to the identification of test case pairs, which are eminently suitable for merging. In this paper, we fill this gap by presenting a novel approach that helps identifying those test case pairs within a given set of systematically generated test cases which, when merged, have potential for high test suite reduction. As a result, test suites reduced by our approach are considerably smaller in size than those, whose pairs are selected randomly.