A Test Suite Reduction Method Based on Novel Quantum Ant Colony Algorithm

Test Suite Reduction is to find a subset of the original test suite which contains less test cases than original one but covers the same test request. In order to reduce the size of the data processed by Ant Colony Algorithm, this paper firstly chooses the test case set to form a candidate set. Then, based on the ant colony algorithm, QEA (Quantum-inspired Evolutionary Algorithm) and quantum revolving gate are introduced. The advantages of entanglement and coherence of quantum computation are introduced. In addition, we propose a Test Suite Reduction method based on Modified Quantum Ant Colony Algorithm. Finally we make quantity of simulation experiments compared the result of other algorithms, we find that the modified quantum ant colony system can solve the problem more efficiently and perform much better.