Diagnosis of Delay Defects Using Statistical Timing Models

V
VTS
2003
21st IEEE VLSI Test Symposium
Abstract - Diagnosis of Delay Defects Using Statistical Timing Models

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Angela Krstic Articles by Li-C. Wang Articles by Kwang-Ting Cheng Articles by Jing-Jia Liou

21st IEEE VLSI Test Symposium

Napa Valley, California

April 27-May 01

ISBN: 0-7695-1924-5

	ASCII Text	x
	Angela Krstic, Li-C. Wang, Kwang-Ting Cheng, Jing-Jia Liou, "Diagnosis of Delay Defects Using Statistical Timing Models," VLSI Test Symposium, IEEE, pp. 339, 21st IEEE VLSI Test Symposium, 2003.

	BibTex	x
	@article{ 10.1109/VTEST.2003.1197672, author = {Angela Krstic and Li-C. Wang and Kwang-Ting Cheng and Jing-Jia Liou}, title = {Diagnosis of Delay Defects Using Statistical Timing Models}, journal ={VLSI Test Symposium, IEEE}, volume = {0}, year = {2003}, issn = {1093-0167}, pages = {339}, doi = {http://doi.ieeecomputersociety.org/10.1109/VTEST.2003.1197672}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - VLSI Test Symposium, IEEE TI - Diagnosis of Delay Defects Using Statistical Timing Models SN - 1093-0167 SP EP A1 - Angela Krstic, A1 - Li-C. Wang, A1 - Kwang-Ting Cheng, A1 - Jing-Jia Liou, PY - 2003 KW - null VL - 0 JA - VLSI Test Symposium, IEEE ER -

Angela Krstic, University of California, Santa Barbara

Li-C. Wang, University of California, Santa Barbara

Kwang-Ting Cheng, University of California, Santa Barbara

Jing-Jia Liou, National Tsing-Hua University, Taiwan

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/VTEST.2003.1197672

In this paper, we study the problem of delay defect diagnosis based on statistical timing models. We propose a diagnosis algorithm that can effectively utilize statistical timing information based upon single defect assumption. We evaluate its performance and its applicability to single as well as multiple defect scenarios via statistical defect injection and simulation. With a statistical timing analysis framework developed in the past, we demonstrate the new concept in statistical delay defect diagnosis, and discuss experimental results using benchmark circuits.

Citation:

Angela Krstic, Li-C. Wang, Kwang-Ting Cheng, Jing-Jia Liou, "Diagnosis of Delay Defects Using Statistical Timing Models," vts, pp.339, 21st IEEE VLSI Test Symposium, 2003

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.