Abstract: The generation of test cases is the key to combinational test. By constructing the search model of combinatorial space, a new test suite minimization method is presented based on ant colony algorithm merging differential evolution with dynamic heuristic information. The new method overcomes the premature convergence effectively. Through the experiment, it is verified that DEACA produces more optimal test suite than the original method ACA and has some merits compared with other methods.

Key words: combinatorial test, test case, ant colony algorithm, differential evolution, dynamic heuristic information

摘要： 针对组合测试中测试用例集生成这一关键问题，通过构建组合空间的搜索模型，提出了一种用于求解最小测试用例集的差分进化蚁群算法（DEACA）。该算法将差分进化融入到蚁群算法中，并在搜索过程中动态更新启发信息，有效克服了标准蚁群算法在求解组合用例时出现的早熟现象。实验表明该方法优于标准蚁群算法，与其他方法相比也具有一定优势和特点。

关键词: 组合测试, 测试用例, 蚁群算法, 差分进化, 动态启发信息