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We introduce a two-staged Genetic Algorithm for optimizing weighted random pattern testing in a Built-InSelf-Test (BIST) environment. The first stage includes the OBDD-based optimization of input probabilities with regard to the expected test length. The optimization itself is constrained to discrete weight values which can directly be integrated in a BIST(More)
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