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On candidate fault sets for fault diagnosis and dominance graphs of equivalence classes

机译:关于用于故障诊断的候选故障集和等价类的优势图

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The goal of fault diagnosis is to identify a set of candidate faults, or fault locations, that explain an observed faulty output response of a chip. In fault diagnosis procedures that are based on specific fault models, a scoring algorithm can be used for defining sets of candidate faults that include the faults with the highest scores. This paper shows that it is possible to capture the underlying concepts that make fault scoring effective through a graph, which is referred to as the dominance graph. With a test set T used for fault diagnosis, the graph represents the dominance relations between the equivalence classes obtained with respect to T. The observed response Robs of a chip-under-diagnosis is associated with an equivalence class Cobs, and Cobs is added to the dominance graph. A candidate fault set is defined based on the dominance relations that are added to the graph due to the addition of Cobs. Certain properties of these dominance relations point to the type of the defect present in the chip, and the most appropriate algorithm for defining a set of candidate faults based on it.
机译:故障诊断的目的是确定一组候选故障或故障位置,这些故障或故障位置可以解释观察到的芯片故障输出响应。在基于特定故障模型的故障诊断过程中,可以使用评分算法来定义候选故障集,其中候选故障集包括得分最高的故障。本文表明,可以通过图(称为优势图)来捕获使故障评分有效的基本概念。对于用于故障诊断的测试集T,该图表示相对于T获得的等价类之间的优势关系。观察到的诊断不足芯片的响应R obs 与等价关联C obs 类和C obs 被添加到优势图中。基于由于添加了C obs 而添加到图中的优势关系来定义候选故障集。这些优势关系的某些特性指向芯片中存在的缺陷的类型,以及基于该缺陷定义一组候选故障的最合适算法。

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