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When Optimized N-Detect Test Sets are Biased: An Investigation of Cell-Aware-Type Faults and N-Detect Stuck-At ATPG

机译:优化的N检测测试集有偏置:对ATPG的细胞感知型故障和N检测的调查

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Cell-aware faults have previously been proposed to more effectively detect defects within gates. At the same time, n-detect test sets that provide multiple detections of each stuck-at fault are often used to maximize the detection of unmodeled defects. However, n-detect test sets are often not particularly effective at fortuitously detecting all untargeted cell-aware faults. In this paper, we investigate the effectiveness of different types of n-detect ATPG test sets for efficiently detecting difficult cellaware-type faults and explain why optimizing test sets for n- detect using stuck-at faults while still keeping pattern counts low can actually bias those test sets against the detection of some cell-aware type faults. We then investigate the addition of cellaware top-off patterns for cell-aware-type faults that are shown to be functionally relevant through good state simulation, allowing such faults to be prioritized when testing resources are limited.
机译:先前已经提出了细胞感知故障以更有效地检测门内的缺陷。同时,正常使用提供多个粘土故障检测的n检测测试集来最大化未拼质缺陷的检测。然而,N检测测试集通常在偶然检测所有未标准的单元感知故障时往往特别有效。在本文中,我们调查了不同类型的N检测ATPG测试集的有效性,以便有效地检测困难的秘密型故障,并解释为什么使用卡在故障时优化测试集的测试集,同时仍然保持模式计数低实际上偏差这些测试集针对检测一些细胞感知类型故障。然后,我们调查用于通过良好状态模拟所示在功能相关的细胞感知型故障的Cellaware级别故障的添加,允许在测试资源有限时优先考虑这些故障。

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