Forecasting and Evaluating the Efficiency of Test Generation Algorithms by Genetic Algorithm

摘要

To generate a test set for a given circuit (including both combinational and sequential circuits), choice of an algorithm within a number of existing test generation algorithms to apply is bound to vary from circuit to circuit. In this paper, the genetic algorithms are used to construct the models of existing test generation algorithms in making such choice more easily. Therefore, we may forecast the testability parameters of a circuit before using the real test generation algorithms. Experimental results are given to convince the readers of the turth and the usefulness of this approach.