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蒙特卡洛工艺变化分析×自动测试向量生成×
领域电气工程电气工程
方法族Process / pipelineProcess / pipeline
起源年份20031966
提出者George S. Fishman, Sani R. NassifJ. Paul Roth
类型Probabilistic modeling of semiconductor manufacturing variabilityAutomated fault-detection test vector generation
开创性文献Fishman, G. S. (1996). Monte Carlo: Concepts, Algorithms, and Applications. Springer-Verlag. DOI ↗Abramovici, M., Breuer, M. A., & Friedman, A. D. (1990). Digital Systems Testing and Testable Design. Computer Science Press. link ↗
别名Monte Carlo simulation, Process variation analysis, PVT analysisATPG, Test pattern generation, Fault-based testing
相关33
摘要Monte Carlo Process Variation analysis quantifies the impact of manufacturing uncertainties on circuit performance using statistical sampling. As semiconductor technology scales, process variations (gate length, oxide thickness, dopant fluctuations) create significant uncertainties in delay, power, and leakage. Monte Carlo methods sample the random variation space, enabling statistical characterization of yield, timing margins, and reliability. Essential for modern technology nodes.Automatic Test Pattern Generation (ATPG) is the automated creation of test vectors that detect manufacturing defects in digital circuits. Pioneered by Roth in 1966, ATPG systematically finds inputs that make stuck-at faults observable at outputs, enabling comprehensive fault detection. ATPG is critical for semiconductor manufacturing: enabling high test coverage ensures only good chips ship and identifies manufacturing process issues.
ScholarGate数据集
  1. v1
  2. 3 来源
  3. PUBLISHED
  1. v1
  2. 3 来源
  3. PUBLISHED

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ScholarGate方法对比: Monte Carlo Process Variation · Automatic Test Pattern Generation. 于 2026-06-15 检索自 https://scholargate.app/zh/compare