实际使用顺序ATPG进行模型检查:付出额外的努力是值得的

M. Hsiao, J. Jain
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引用次数: 14

摘要

我们提出了一个基于仿真的自动测试模式生成(ATPG)的实际应用研究,用于大型顺序电路的模型检查。初步研究表明,逐步建立并学习状态空间的atpg具有在不需要完整状态空间信息的情况下实现验证目标的潜力。验证一组有用属性的成功依赖于ATPG的性能和容量。我们比较了一个只有激发的ATPG和一个同时进行激发和传播的ATPG。尽管仅激励策略足以证明目标是正确的,但与仅激励策略相比,激励-传播ATPG实现了更高的信号证明覆盖率。这是因为只有激励的ATPG无法获得有助于遍历状态空间的相关状态信息,从而导致ATPG放弃目标。我们的实验表明,通过传播学习到的不完整但有用的信息会对模型检查的ATPG性能产生重大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Practical use of sequential ATPG for model checking: going the extra mile does pay off
We present a study of the practical use of a simulation-based automatic test pattern generation (ATPG) for model checking in large sequential circuits. Preliminary findings show that ATPGs which gradually build and learn from the state-space has the potential to achieve the verification objective without needing the complete state-space information. The success of verifying a useful set of properties relies on the performance and capacity of ATPG. We compared an excitation-only ATPG with one that performs both excitation and propagation. Even though the excitation-only strategy suffices to justify the objective, the excitation-and-propagation ATPG achieved higher signal-justification coverages than the excitation-only counterpart. This is because excitation-only ATPG falls short in obtaining pertinent state information helpful for traversing the state space, resulting in ATPG aborting the objective. Our experiments demonstrated that incomplete but useful information learned via propagation can have significant impact on the performance of ATPG for model-checking.
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