基于组合故障频繁树的最小失效诱因模式定位方法

Locating minimal failure-causing schema based on combinatorial fault frequent tree

针对定位实际软件中最小失效诱因模式可能受到屏蔽效应影响的问题,提出了一种基于组合故障频繁树的最小失效诱因模式定位方法及其迭代框架.该方法首先依据组合测试用例集及测试结果构建组合故障频繁树,然后从组合故障频繁树中抽取频繁参数值组合作为可疑失效诱因模式,并根据其可疑得分进行排序.基于给出的失效诱因模式迭代定位框架,反复迭代直到满足某一个停止准则为止.利用仿真实验对存在和不存在掩蔽效应影响的2种情形进行有效性验证.实验结果表明,在这2种情形下所提方法均能定位最小失效诱因模式,有效减少附加测试用例的数目.

To solve the problem that a minimal failure-causing schema(MFS)in actual software may be influenced by masking effects,a locating MFS technique based on the combinatorial fault frequent tree(CFF-tree)and the corresponding iterative framework are proposed.First,a CFF-tree is constructed based on the combination test suite and the test results.Then,the frequent parameter combination of the tree is extracted as the MFS and ranked according to the suspiciousness score.Based on the locating MFS iterative framework,the process repeats until a stop criterion is satisfied.The simulation experiments are carried out to validate the effectiveness of the method in the two cases with and without masking effects.The experimental results show that in these two cases the proposed method can locate MFS and effectively reduce the number of the additional test cases.