DocumentCode
1915096
Title
A new multiple weight set calculation algorithm
Author
Hong-Sik Kirn ; Lee, Jin-kyue ; Kang, Sungho
Author_Institution
Dept. of Electr. Eng., Yonsei Univ., Seoul, South Korea
fYear
2001
fDate
2001
Firstpage
878
Lastpage
884
Abstract
The number of weighted random patterns depends on the sampling probability of the corresponding deterministic test pattern. Therefore if the weight set is extracted from the deterministic pattern set with high sampling probabilities, the test length can be shortened. In this paper we present a new multiple weight set generation algorithm that generates high performance weight sets by removing deterministic patterns with low sampling probabilities. In addition, the weight set that makes the variance of sampling probabilities for deterministic test patterns small, reduces the number of the deterministic test patterns with low sampling probability. Henceforth we present a new weight set calculation algorithm that uses the optimal candidate list and reduces the variance of the sampling probability. The results on ISCAS 85 and ISCAS 89 benchmark circuits prove the effectiveness of the new weight set calculation algorithm
Keywords
VLSI; automatic test pattern generation; built-in self test; design for testability; integrated circuit testing; logic testing; probability; ATPG; BIST pattern generator; DFT technique; VLSI circuits; built-in self test; deterministic test pattern; high performance weight sets; multiple weight set calculation algorithm; multiple weight set generation algorithm; sampling probability; test length reduction; weighted random patterns; Automatic test pattern generation; Built-in self-test; Circuit faults; Circuit testing; Design for testability; Logic testing; Probabilistic logic; Probability; Sampling methods; Test pattern generators;
fLanguage
English
Publisher
ieee
Conference_Titel
Test Conference, 2001. Proceedings. International
Conference_Location
Baltimore, MD
ISSN
1089-3539
Print_ISBN
0-7803-7169-0
Type
conf
DOI
10.1109/TEST.2001.966710
Filename
966710
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