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ITC
2003
IEEE

Using Logic Models To Predict The Detection Behavior Of Statistical Timing Defects

14 years 4 months ago
Using Logic Models To Predict The Detection Behavior Of Statistical Timing Defects
In this paper, we study the possibility of using logic defect-level prediction models to predict the detection behavior of statistical timing defects. We compare two known logic models: the Williams-Brown (WB) model and the Mercer-Park-GrimailaDworak (MPGD) model. In the WB-model, the defect coverage is replaced by the n-detection transition fault coverage. We first demonstrate that both logic models may fail to predict the detection of statistical timing defects. Then, we propose an improved WB model based upon selection of the hard-to-detect transition faults. We show that, by selecting a proper subset of the hard-to-detect transition faults, the detection behavior of these faults can correlate well to the detection behavior of statistical timing defects. We explain our findings through statistical delay defect injection and simulation, and report results based upon various benchmark circuits.
Li-C. Wang, Angela Krstic, Leonard Lee, Kwang-Ting
Added 04 Jul 2010
Updated 04 Jul 2010
Type Conference
Year 2003
Where ITC
Authors Li-C. Wang, Angela Krstic, Leonard Lee, Kwang-Ting Cheng, M. Ray Mercer, Thomas W. Williams, Magdy S. Abadir
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