Multidimensional analog test metrics estimation using extreme value theory and statistical blockade

The high cost of testing certain analog, mixed-signal, and RF circuits has driven in the recent years the development of alternative low-cost tests to replace the most costly or even all standard specification tests. However, there is a lack of solutions for evaluating the parametric test error, that is, the test error for circuits with process variations, resulting from this replacement. For this reason, test engineers are often reluctant to adopt alternative tests since it is not guaranteed that test cost reduction is not achieved at the expense of sacrificing test quality. In this paper, we present a technique to estimate the parametric test error fast and reliably with parts per million accuracy. The technique is based on extreme value theory and statistical blockade. Relying on a small number of targeted simulations, it is capable of providing accurate estimates of parametric test error in the general scenario where a set of alternative tests replaces all or a subset of standard specification tests.