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On N-detect pattern set optimization

机译:关于N检测模式集优化

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In this paper, we illustrate that the traditional N-detect ATPG is unoptimized in terms of the size of the generated pattern set. The optimization problem is formulated as a minimum covering problem. Integer linear programming (ILP) is applied to obtain an N-detection ATPG pattern set with the minimum number of patterns. A heuristic method is also proposed to obtain sub-optimal solutions efficiently. Experimental results demonstrate that by using the proposed method, the number of N-detection patterns can be reduced by about 18% for N=3 and about 13% for N=5 without compromising N-detection objective
机译:在本文中,我们说明了在生成的模式集的大小方面,传统的N检测ATPG未得到优化。将优化问题表述为最小覆盖问题。应用整数线性编程(ILP)可获得具有最少数量模式的N检测ATPG模式集。还提出了一种启发式方法来有效地获得次优解。实验结果表明,该方法可以在不影响N检测目标的情况下,将N = 3的N检测模式数量减少约18%,N = 5的N检测模式数量减少约13%。

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