TEA:具有时序异常设计的测试生成算法

Naixing Wang, Chen Wang, Kun-Han Tsai, Wu-Tung Cheng, X. Lin, M. Kassab, I. Pomeranz
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引用次数: 4

摘要

定时异常通常用于表示某些路径的定时已经放松,以便使设计能够满足定时关闭。生成基于扫描的测试模式而不考虑定时异常会导致无效的测试响应,从而导致不可预测的测试质量影响。现有的基于仿真的解决方案在生成测试模式后屏蔽掉不可靠的信号。如果检测目标故障所需的信号不可靠且被屏蔽,则生成的测试模式无法检测到目标故障,将被丢弃。为了获得可接受的测试覆盖率,通常需要使用随机决策过程对测试生成进行多次迭代,其中为目标错误生成不同的测试。本文提出了一种创新的确定性ATPG算法TEA (Timing Exception ATPG),以防止生成的测试模式受到时序异常的影响。该确定性算法与现有的基于仿真的方法兼容。在这个模拟环境中,TEA是完整的,对于目标故障,生成的测试模式可以保证检测到它。如果不能使用TEA生成测试模式,则给定设计和现有仿真环境中的定时异常路径,目标故障是不可测试的。与现有的基于仿真的方法相比,使用TEA可以生成更有效的测试集,显著提高测试覆盖率、测试模式计数和总ATPG运行时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TEA: A Test Generation Algorithm for Designs with Timing Exceptions
Timing exceptions are commonly used to indicate that the timing of certain paths have been relaxed so as to enable the design to meet timing closure. Generating scan-based test patterns without considering timing exceptions can lead to invalid test responses, resulting in unpredictable test quality impact. The existing simulation-based solution masks out unreliable signals after a test pattern is generated. If the signals required for detecting the target fault are unreliable and masked out, the generated test pattern fails to detect the target fault, and it is discarded. To achieve an acceptable test coverage, several iterations of test generation with a randomized decision-making process are typically required where different tests are generated for target faults. In this paper, an innovative deterministic ATPG algorithm called TEA (Timing Exception ATPG) is proposed to prevent the generated test patterns from being impacted by timing exceptions. The deterministic algorithm is compatible with the existing simulation-based approach. In this simulation environment, TEA is complete such that for a target fault, the test pattern generated is guaranteed to detect it. If a test pattern cannot be generated using TEA, the target fault is untestable given the timing exception paths in the design and the existing simulation environment. Compared to the existing simulation-based approach, using TEA can generate a more effective test set, improving test coverage, test pattern count, and the total ATPG run time significantly.
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