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, GA-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 GA-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.

Date Published: 13 October 1998
PDF: 12 pages
Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); doi: 10.1117/12.326704

Published in SPIE Proceedings Vol. 3455:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)