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Forecasting the efficiency of test generation algorithms for digital circuits

机译:预测数字电路测试生成算法的效率

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Within this era of VLSI circuits, testability is truly a very crucial issue. 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 algorithm. The results also can be used to evaluate the efficiency of the existing test generation algorithms. Experimental results are given to confirm the validity and usefulness of this approach.
机译:在VLSI电路的这一时代内,可测试性真正是一个非常重要的问题。为了为给定电路(包括组合和顺序电路包括组合电路)来生成测试集,在许多现有的测试生成算法中选择算法恰好地从电路到电路都变化。在本文中,遗传算法用于构建现有测试生成算法的模型,使得更容易制作这种选择。因此,我们可以在使用真实测试生成算法之前预测电路的可测试性参数。结果还可用于评估现有测试生成算法的效率。给出了实验结果证实了这种方法的有效性和有用性。

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