Fault Collapsing Using a Novel Extensibility Relation

M. Chandrasekar, M. Hsiao
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引用次数: 1

Abstract

Fault Collapsing of a target fault-list can help in obtaining a compact test set, decreasing test-generation/fault simulation time, and indirectly reducing test data volume and test application time during Manufacturing Test. These factors have a direct impact on test economics, thus obtaining a compact fault list is essential. In this paper, we propose a novel extensibility relation that aids in identifying non-trivial dominance relationships among fault-pairs. We show that our technique supersedes existing dominance-based collapsing techniques and thus may identify more dominance relations among faults. To this end, we learn several necessary assignments for faults in a low-cost fault independent manner, in which memory requirements are also low. Further, from a theoretical point of interest, we theorize a lower bound on the size of a collapsed fault-list. Experimental results on ISCAS85 and full-scan versions of ISCAS89 circuits indicate that, on an average, our technique can eliminate 5% of faults from the collapsed fault list reported by the best known fault collapsing engine. Further, our technique consumed only 2% -4% of the memory used by the best known engine, which also provided for a 2:3x average speed-up!
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基于新型可拓关系的断层塌陷
对目标故障列表进行故障折叠,可以获得紧凑的测试集,减少测试生成/故障模拟时间,间接减少制造测试过程中的测试数据量和测试应用时间。这些因素对试验经济性有直接影响,因此获得一个紧凑的故障列表是必要的。在本文中,我们提出了一种新的可扩展关系,它有助于识别故障对之间的非平凡优势关系。我们表明,我们的技术取代了现有的基于优势的崩溃技术,因此可以识别更多的断层之间的优势关系。为此,我们以低成本的故障无关方式学习了一些必要的故障赋值,其中内存需求也很低。进一步,从理论的角度出发,我们理论化了崩溃故障表大小的下界。在ISCAS85和ISCAS89全扫描版电路上的实验结果表明,我们的技术平均可以从目前最著名的故障崩溃引擎报告的故障列表中消除5%的故障。此外,我们的技术只消耗了最著名引擎所使用的2% -4%的内存,这也提供了2:3的平均加速!
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