Evolutionary Approach to Test Generation for Functional BIST
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In the paper, an evolutionary approach to test generation for functional BIST is considered. The aim of the proposed scheme is to minimize the test data volume by allowing the device's microprogram to test its logic, providing an observation structure to the system, and generating appropriate test data for the given architecture. Two methods of deriving a deterministic test set at functional level are suggested. The first method is based on the classical genetic algorithm with binary and arithmetic crossover and mutation operators. The second one uses genetic programming, where test is represented as a sequence of microoperations. In the latter case, we apply two-point crossover based on exchanging test subsequences and mutation implemented as random replacement of microoperations or operands. Experimental data of the program realization showing the efficiency of the proposed methods are presented.
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