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Deep Learning Based Test Compression Analyzer
Deep Learning Based Test Compression Analyzer
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机译:基于深度学习的测试压缩分析器
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摘要
One or more machine-learning models are trained and employed to predict test coverage and test data volume. Input features for the one or more machine-learning models comprise the test configuration features and the design complexity features. The training data are prepared by performing test pattern generation and circuit design analysis. The design complexity features may comprise testability, X-profiling, clock domains, power domains, design-rule-checking warnings, or any combination thereof.
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