Worst-case test vectors generation using genetic algorithms for the detection of total-dose induced leakage current failures

H. A. Abdel-Aziz, M. M. Abdel-Aziz, A. Wassal, A. Abou-Auf
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Abstract

In this paper, we develop a methodology for generating the worst-case test vectors (WCTV) necessary to detect leakage current failures in a standard-cell based ASIC device exposed to a total ionizing dose. The methodology is based on using the genetic algorithm technique and as such it produces a near worst-case vector. The methodology is validated experimentally by applying the generated vectors on a test chip after exposure to total dose. In terms of total-dose induced leakage current failures, experiments shown that the near worstcase vector results are very close to those of the worst-case vector.
基于遗传算法的最坏情况测试向量生成方法用于总剂量感应泄漏电流故障检测
在本文中,我们开发了一种生成最坏情况测试向量(WCTV)的方法,该方法用于检测暴露于总电离剂量下的基于标准电池的ASIC器件中的泄漏电流故障。该方法是基于使用遗传算法技术,因此它产生了一个接近最坏情况的向量。在总剂量暴露后,将生成的载体应用于测试芯片上,实验验证了该方法。对于总剂量引起的泄漏电流失效,实验表明,近最坏情况向量的结果与最坏情况向量的结果非常接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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