EAGLE: A regression model for fault coverage estimation using a simulation based metric
Shahrzad Mirkhani, Jacob A. Abraham · 2014
Evaluating the fault coverage of manufacturing tests has become a time-consuming process due to today's large and complex digital designs. The computation cost is even more pronounced in software-based self test, on-line test, and logic BIST schemes, which require fault simulation of sequential circuits. In this paper, we build a regression model for estimating stuck-at fault coverage. This model is built based on partial fault simulation along with a statistical metric, which is calculated by a single pass of fault-free simulation. Our results on ISCAS'85, ISCAS'89, and the OR1200 processor show that by only fault simulating 7.6% of the test vectors, on average, over 94% of the fault coverage bounds are estimated correctly.