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A fault avoidance approach with test set generation in combinational circuits using genetic algorithm

机译:基于遗传算法的组合电路测试集生成的故障避免方法

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In this paper a stuck-at-fault avoidance approach in combinational VLSI circuits using genetic algorithm (GA) by comparing two complementary circuits has been proposed. Analysis of whole test set generation for a fault model helps to reduce the fault detection probability in combinational circuits. The GA proves to be a very helpful algorithm in finding the highest suitable number of test patterns in reference to most suitable solution for any problem. The paper focuses on detectability concept which is a way to find out the fault present in the circuit. Undetectability is a way to avoid the detected fault which is present in the circuit. In this paper we are taking the complementary circuit of reference fault model and analyzing the results for both circuits by generating test sets. In this paper results are obtained for single stuck-at-fault in the ISIS PROTEUS (C12) benchmark circuit. Experimental results showed that the genetic algorithm is helpful in findings the best method to avoid fault in terms of fault coverage and fitness factor.
机译:通过比较两个互补电路,提出了一种采用遗传算法(GA)的组合VLSI电路中的一种避免故障的方法。对故障模型的整个测试集生成进行分析有助于降低组合电路中的故障检测概率。事实证明,遗传算法是一种非常有用的算法,它可以针对任何问题的最合适的解决方案,找到最合适数量的测试模式。本文关注可检测性概念,这是一种找出电路中存在的故障的方法。不可检测性是一种避免电路中存在检测到的故障的方法。在本文中,我们采用参考故障模型的互补电路,并通过生成测试集来分析两个电路的结果。在本文中,获得了ISIS PROTEUS(C12)基准电路中单次卡死的结果。实验结果表明,从故障覆盖率和适应度角度出发,遗传算法有助于发现避免故障的最佳方法。

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