Paper Info
Title
An Architecture of Embedded Decompressor with Reconfigurability for Test Compression
Abstract
Test compression / decompression scheme for reducing the test application time and memory requirement of an LSI tester has been proposed. In the scheme, the employed coding algorithms are tailored to a given test data, so that the tailored coding algorithm can highly compress the test data. However, these methods have some drawbacks, e.g., the coding algorithm is ineffective in extra test data except for the given test data. In this paper, we introduce an embedded decompressor that is reconfigurable according to coding algorithms and given test data. Its reconfigurability can overcome the drawbacks of conventional decompressors with keeping high compression ratio. Moreover, we propose an architecture of reconfigurable decompressors for four variable-length codings. In the proposed architecture, the common functions for four codings are implemented as fixed (or non-reconfigurable) components so as to reduce the configuration data, which is stored on an ATE and sent to a CUT. Experimental results show that (1) the configuration data size becomes reasonably small by reducing the configuration part of the decompressor, (2) the reconfigurable decompressor is effective for SoC testing in respect of the test data size, and (3) it can achieve an optimal compression of test data by Huffman coding.
Year
DOI
Venue
2008
10.1093/ietisy/e91-d.3.713
IEICE Transactions
Keywords
Field
DocType
extra test data,tailored coding algorithm,test compression,test application time,huffman coding,test data,test data size,configuration data,coding algorithm,configuration data size,compression ratio,variable length code,huffman codes
Reconfigurability,Computer science,Coding (social sciences),Huffman coding,Artificial intelligence,Computer hardware,Variable-length code,System on a chip,Pattern recognition,Compression ratio,Test data,Test compression,Embedded system
Journal
Volume
Issue
ISSN
E91-D
3
1745-1361
Citations 
PageRank 
References 
0
0.34
8
Authors
3
Name
Order
Citations
PageRank
Hideyuki Ichihara19618.92
Tomoyuki Saiki210.70
Tomoo Inoue335247.23