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.

• 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
• Keywords: Detection Behavior, Hardware, ITC 2003, Statistical Timing Defects, Transition Faults