DocumentCode :
3378624
Title :
Experience with biased random pattern generation to meet the demand for a high quality BIST
Author :
Gruetzner, Matthias ; Starke, Cordt W.
Author_Institution :
IBM Lab. Boeblingen, Germany
fYear :
1993
fDate :
19-22 Apr 1993
Firstpage :
408
Lastpage :
417
Abstract :
Three different approaches for LFSR based biased random pattern generation are presented. They can be mapped into custom-made finite state machines satisfying the requirements for BIST. The first approach chooses patterns with constant weights for all PIs/SRLs. The second one uses weights for clusters of inputs. Weights determined from design analysis are applied by a `rotation´ algorithm to cover the highest number of possible faults with simple ring shifters. As a result of these two heuristics, the fault coverage is improved up to 2%. Both approaches require <1% hardware overhead. This was demonstrated for two CMOS VLSI chips. The third approach uses a weight merging algorithm, in which an optimal weight set is determined by merging previously calculated optimal weights for the random pattern resistant faults. This leads to a fault coverage of approximately 99% with an acceptable amount of hardware as is demonstrated for one VLSI chip
Keywords :
CMOS integrated circuits; VLSI; built-in self test; fault location; finite state machines; integrated logic circuits; logic testing; random processes; BIST; CMOS VLSI chips; biased random pattern generation; clusters of inputs; constant weights; custom-made finite state machines; design analysis; fault coverage; fault location; optimal weight set; random pattern resistant faults; ring shifters; rotation algorithm; weight merging algorithm; Algorithm design and analysis; Automatic testing; Built-in self-test; Clustering algorithms; Hardware; Laboratories; Logic testing; Merging; System testing; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
European Test Conference, 1993. Proceedings of ETC 93., Third
Conference_Location :
Rotterdam
Print_ISBN :
0-8186-3360-3
Type :
conf
DOI :
10.1109/ETC.1993.246584
Filename :
246584
Link To Document :
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