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Experiences in the use of evolutionary techniques for testing digital circuits

Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, SPIE 1998 Annual Meeting

Invited paper

ABSTRACT

The generation of test patterns for sequential circuits is one of the most challenging problems arising in the field of Computer-Aided Design for VLSI circuits. In the past decade, Genetic Algorithms have been deeply investigated as a possible approach: several algorithms have been described, and significant improvements have been proposed with respect to their original versions. As a result, Genetic Algorithm-based test pattern generators can now effectively compete with other methods, such as topological or symbolic ones. This paper discusses the advantages and disadvantages of GA-based approaches and describes GATTO, a state-of-the-art Genetic Algorithm-based test pattern generator. Other algorithms belonging to the same category are outlined as well. The paper puts GATTO and other GA-based tools in perspective, and shows that Evolutionary Computation techniques can successfully compete with more traditional approaches, or be integrated with them.


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[CSRe98] F. Corno, M. Sonza Reorda, M. Rebaudengo, "Experiences in the use of evolutionary techniques for testing digital circuits," Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, SPIE 1998 Annual Meeting