布尔规格的最小故障导致模式定位方法

Tianyu Xu, Guanglin Li, Jun Lu, Ziyuan Wang
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引用次数: 0

摘要

基于宽度优先选择策略的关系树模型(BFSTRT)故障定位方法是最小故障导致模式(MFS)的最佳定位方法。但是,BFSTRT的缺点是无法解决“额外的测试用例引入新的故障模式”的情况,并且由于基于关系树模型的故障定位方法是在构建模型树时一次性生成故障测试用例的所有子模式,因此这种类型的故障定位方法消耗的内存空间很大。本文提出了一种针对布尔规范(BELF)方法的最小故障导致模式定位方法,有效地解决了BFSTRT的上述两个不足。实验结果表明,BELF在定位精度和查全率方面都优于BFSTRT。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Approach of Locating Minimal Failure-Causing Schema for Boolean-Specifications
The fault location method of relational tree model (BFSTRT) based on the breadth-first selection strategy is the best in locating the Minimal Failure-causing Schema (MFS). However, the BFSTRT has a defect that it cannot solve the situation of “additional test cases introduce new failure modes”, moreover, since the fault location method based on the relational tree model is to generate all sub patterns of the failure test case at one time when building the model tree, so this type of fault location method consumes large memory space. This paper proposes an Approach of Locating Minimal Failure-causing Schema for Boolean-Specification (BELF) method, which effectively solves the above two deficiencies in BFSTRT. The experimental results show that the localization efficiency of BELF is better than BFSTRT in terms of precision and recall.
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