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Success-Driven Learning in ATPG for Preimage Computation
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MDT.2004.97November/December 2004 (vol. 21 no. 6) pp. 504-512
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Shuo Sheng, Michael S. Hsiao, "Success-Driven Learning in ATPG for Preimage Computation," IEEE Design and Test of Computers, vol. 21, no. 6, pp. 504-512, November/December, 2004.
 
 
BibTex
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@article{ 10.1109/MDT.2004.97,
author = {Shuo Sheng and Michael S. Hsiao},
title = {Success-Driven Learning in ATPG for Preimage Computation},
journal ={IEEE Design and Test of Computers},
volume = {21},
number = {6},
issn = {0740-7475},
year = {2004},
pages = {504-512},
doi = {http://doi.ieeecomputersociety.org/10.1109/MDT.2004.97},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - MGZN
JO - IEEE Design and Test of Computers
TI - Success-Driven Learning in ATPG for Preimage Computation
IS - 6
SN - 0740-7475
SP504
EP512
EPD - 504-512
A1 - Shuo Sheng,
A1 - Michael S. Hsiao,
PY - 2004
VL - 21
JA - IEEE Design and Test of Computers
ER -
 
Shuo Sheng, Mentor Graphics
Michael S. Hsiao, Virginia Tech
Editor's note: Unbounded model checking fundamentally requires either image or preimage calculations. This article introduces a hybrid method for making preimage calculations using ATPG and binary decision diagrams (BDDs). Experimental results show that the proposed method achieves a speedup of two to three orders of magnitude over pure ATPG methods. —Carl Pixley, Synopsys
Citation:
Shuo Sheng, Michael S. Hsiao, "Success-Driven Learning in ATPG for Preimage Computation," IEEE Design and Test of Computers, vol. 21, no. 6, pp. 504-512, Nov./Dec. 2004, doi:10.1109/MDT.2004.97
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