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A hybrid scheme for compacting test responses with unknown values
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Source International Conference on Computer Aided Design archive
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design table of contents
San Jose, California
SESSION: Test compression and test power table of contents
Pages 513-519  
Year of Publication: 2007
ISBN ~ ISSN:1092-3152 , 1-4244-1382-6
Authors
Mango C.-T. Chao  National Chiao Tung Univ., Hsinchu, Taiwan
Kwang-Ting Cheng  UC Santa Barbara, Santa Barbara, CA
Seongmoon Wang  NEC Labs. America, Princeton, NJ
Srimat T. Chakradhar  NEC Labs. America, Princeton, NJ
Wen-Long Wei  NEC Labs. America, Princeton, NJ
Sponsors
: IEEE CASS/CANDE
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CS\DATC : IEEE Computer Society
CEDA : Council on Electronic Design Automation
Publisher
IEEE Press  Piscataway, NJ, USA
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Downloads (6 Weeks): 1,   Downloads (12 Months): 13,   Citation Count: 0
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ABSTRACT

This paper presents a hybrid compaction scheme for test responses containing unknown values, which consists of a space compactor and an unknown-blocking Multiple Input Signature Registers (MISR). The proposed scheme guarantees no coverage loss for the modeled faults. The proposed hybrid scheme can also be tuned to observe any user-specified percentage of responses for controlling the coverage loss for un-modeled faults. The experimental results demonstrate that, in comparison with a space compactor or an unknown-blocking MISR alone, the hybrid compaction scheme achieves a lower coverage loss without demanding more test-data volume. In addition, we propose a quantitative approach to estimate the required percentage of observable responses for the proposed scheme, directly based on a test-quality metric of un-modeled faults.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Design Compiler, Synopsis Inc., http://www.synopsis.com/.
Collaborative Colleagues:
Mango C.-T. Chao: colleagues
Kwang-Ting Cheng: colleagues
Seongmoon Wang: colleagues
Srimat T. Chakradhar: colleagues
Wen-Long Wei: colleagues