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Genetic algorithm based test pattern generation for multiple stuck-at faults and test power reduction in VLSI circuits

机译:基于遗传算法的多个卡死故障的测试模式生成和VLSI电路的测试功耗降低

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A method of test pattern generation for multiple stuck-at faults in VLSI circuits, using genetic algorithm is proposed. The test patterns were earlier generated for single stuck at faults only but in the proposed work, multiple faults are considered and fault masking is also taken into account when faults are injected. The test patterns to detect the faults are the binary values given as inputs to the circuit under test. These patterns should be compact and also should have minimum switching among them to reduce the test power. Genetic Algorithms (GA) is a search technique to find solutions to optimization and search problems. Hence the proposed work uses GA to generate test patterns. Here the chromosomes in GA are substituted for the test patterns. The test patterns are initialized randomly and their fitness value is evaluated. Now GA operators like selection, crossover and mutation are applied on this initial set to reproduce better test patterns. These generated test patterns are reordered using reordering techniques, don't cares filled by filling techniques to reduce the switching activity among them thus reducing the test power.
机译:提出了一种利用遗传算法生成VLSI电路中多个卡死故障的测试码型的方法。仅针对单个卡在故障处的故障生成了测试模式,但在建议的工作中,考虑了多个故障,并且在注入故障时也考虑了故障屏蔽。用于检测故障的测试模式是作为被测电路输入的二进制值。这些模式应紧凑,并且它们之间的切换应尽可能少,以降低测试功率。遗传算法(GA)是一种搜索技术,用于查找优化和搜索问题的解决方案。因此,建议的工作使用GA生成测试模式。在这里,GA中的染色体被替换为测试模式。随机初始化测试模式,并评估其适用性值。现在,GA操作员(如选择,交叉和变异)将应用于此初始集合,以重现更好的测试模式。使用重新排序技术对这些生成的测试模式进行重新排序,而不必考虑通过填充技术来填充它们,以减少它们之间的切换活动,从而降低测试功率。

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