An alternative view on weighted random pattern testing

This paper describes a new and highly efficient approach for weighted random test pattern generation. In contrast to the state-of-the-art approaches, where input specific weights are computed, the proposed self-test method is tuned on the computation of global, pattern oriented weights: with each weight the generation of the related random test patterns is uniquely specified. The proposed self-test method is based on a partly specified deterministic test pattern set.