当优化的n -检测测试集有偏差时:细胞感知型故障和n -检测卡在ATPG的研究

Fanchen Zhang, Micah Thornton, Jennifer Dworak
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引用次数: 7

摘要

细胞感知故障先前被提出用于更有效地检测门内的缺陷。同时,n-detect测试集提供对每个卡在故障的多个检测,通常用于最大限度地检测未建模的缺陷。然而,n-detect测试集在偶然检测所有非目标细胞感知故障时通常不是特别有效。在本文中,我们研究了不同类型的n检测ATPG测试集在有效检测困难的细胞感知型故障方面的有效性,并解释了为什么在使用卡在故障优化n检测测试集的同时仍然保持低模式计数实际上会使这些测试集对某些细胞感知型故障的检测产生偏差。然后,我们研究了通过良好的状态模拟显示与功能相关的单元感知型故障的单元感知顶掉模式的添加,允许在测试资源有限时对此类故障进行优先级排序。
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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
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 cell-aware-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 cell-aware 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.
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