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Compact dictionaries for fault diagnosis in scan-BIST

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2 Author(s)
Chunsheng Liu ; Dept. of Comput. & Electron. Eng., Nebraska Univ., Lincoln, NE, USA ; Chakrabarty, K.

We present a new technique for generating compact dictionaries for cause-effect fault diagnosis in scan-BIST. This approach relies on the use of three compact dictionaries: 1) D1, containing compacted LFSR signatures for a small number of patterns and faults with high detection probability, 2) an interval-based pass/fail dictionary D2 for the BIST patterns and for faults with relatively lower detection probability, and 3) D3 containing compacted LFSR signatures for clean up ATPG vectors and random-resistant faults. We show that D2, which is two orders of magnitude smaller than a maximal-resolution pass/fail dictionary, provides nearly the same diagnostic resolution as an uncompacted dictionary. We also show that, by using a 16-bit LFSR signature for D1 and D3, we obtain two to three orders of magnitude reduction in dictionary size, yet nearly no loss in diagnostic resolution. Together, these three compact dictionaries provide an. efficient solution to the problem of cause-effect diagnosis in scan-based BIST. These dictionaries can also be used to target unmodeled faults using scoring algorithms.

Published in:

Computers, IEEE Transactions on  (Volume:53 ,  Issue: 6 )

Date of Publication:

June 2004

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