Optimization of Bdd by Chaotic Evolution Algorithm and Its Application in Test of Stuck- Open Faults in Digital Circuits

The binary decision diagram (BDD) is an efficient graph representation of logic Boolean functions, it has wide applications in a lot of areas, such as computer science, circuit design and test. The size of binary decision diagram depends on the variable ordering which is used. A new approach is presented in this paper for the variable ordering and the optimization of binary decision diagrams, the approach is based on a chaotic evolution algorithm. The chaotic evolution algorithm proposed in this paper can combine the features of chaotic systems and evolutionary algorithm, and can take full advantages of both the stochastic properties and the global search ability. The application of the approach for the test of stuck-open faults in digital circuits is investigated, a test algorithm of stuck-open faults is proposed. The experimental results for a lot of digital circuits show that the binary decision diagrams with smaller number of nodes can be obtained by using the approach proposed in this paper, and the test vectors of open faults in digital circuits can be produced.