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On probabilistic testing of large-scale sequential circuits using circuit decomposition

机译:利用电路分解对大型时序电路进行概率测试

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In this paper the detection of permanent faults in sequential circuits by random testing is analyzed utilizing the circuit partitioning approach together with a continuous parameter Markov model. Given a large sequential circuit, it is partitioned into several smaller partitions using either series or parallel decomposition. For each partition with certain stuck faults specified, the original state table and its error version are derived from an analysis of the partition under fault-free and faulty conditions, respectively. A random testing strategy that uses a three-state Markov model is used for detecting permanent stuck faults. Experimentation on various sequential circuits has shown that a significant saving in testing or test generation time can be achieved if we can partition the circuit and then test each of its components as opposed to testing the circuit in its original form.
机译:本文利用电路划分方法和连续参数马尔可夫模型,分析了通过随机测试在顺序电路中永久性故障的检测。给定较大的顺序电路,可使用串联或并联分解将其划分为几个较小的分区。对于指定了某些特定故障的每个分区,原始状态表及其错误版本分别来自在无故障和有故障情况下对该分区的分析。使用三态马尔可夫模型的随机测试策略用于检测永久性卡死故障。在各种时序电路上进行的实验表明,如果我们可以对电路进行分区,然后测试其每个组件,而不是对电路进行原始形式的测试,则可以节省大量的测试或测试生成时间。

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