Improving validation coverage metrics to account for limited observability

In both pre-silicon and post-silicon validation, the detection of design errors requires both stimulus capable of activating the errors and checkers capable of detecting the behavior as erroneous. Most functional and code coverage metrics evaluate only the activation component of the testbench and ignore propagation and detection. In this paper, we summarize our recent work in developing improved metrics that account for propagation and/or detection of design errors. These works include tools for observability-enhanced code coverage and mutation analysis of high-level designs as well as an analytical method, Coverage Discounting, which adds checker sensitivity to arbitrary functional coverage metrics.