Column Parity Row Selection (CPRS) BIST Diagnosis Technique: Modeling and Analysis
IEEE Transactions on Computers
Using reiterative LFSR based X-masking to increase output compression in presence of unknowns
Proceedings of the 18th ACM Great Lakes symposium on VLSI
Scan chain organization for embedded diagnosis
Proceedings of the conference on Design, automation and test in Europe
BISD: scan-based built-in self-diagnosis
Proceedings of the Conference on Design, Automation and Test in Europe
A diagnosis algorithm for extreme space compaction
Proceedings of the Conference on Design, Automation and Test in Europe
Fault diagnosis aware ATE assisted test response compaction
Proceedings of the 16th Asia and South Pacific Design Automation Conference
Construction and Analysis of Augmented Time Compactors
Journal of Electronic Testing: Theory and Applications
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This paper introduces a new class of finite memory compaction schemes called convolutional compactors (CCs). They provide compaction ratios of test responses in excess of 100×, even for a very small number of outputs. This is combined with the capability to detect multiple errors, handling of unknown states, and the ability to diagnose failing scan cells directly from compacted responses. The CCs can also be used to significantly enhance conventional multiple input signature registers. Experimental results presented in the paper demonstrate the efficiency of convolutional compaction for several industrial circuits.