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For many years, the dominant fault model in automatic test pattern
gen eration (ATPG) for digital integrated circuits has been the
stuck-at fault model. The static nature of stuck-at fault testing
when compared to the extremely dynamic nature of integrated circuit
(IC) technology has caused many to question whether or not stuck-at
fault based testing is still viable. Attempts at answering this
question have not been wholly satisfying due to a lack of true
quantification, statistical significance, and/or high computational
expense. In this monograph we introduce a methodology to address
the ques tion in a manner which circumvents the drawbacks of
previous approaches. The method is based on symbolic Boolean
functional analyses using Or dered Binary Decision Diagrams
(OBDDs). OBDDs have been conjectured to be an attractive
representation form for Boolean functions, although cases ex ist
for which their complexity is guaranteed to grow exponentially with
input cardinality. Classes of Boolean functions which exploit the
efficiencies inherent in OBDDs to a very great extent are examined
in Chapter 7. Exact equa tions giving their OBDD sizes are derived,
whereas until very recently only size bounds have been available.
These size equations suggest that straight forward applications of
OBDDs to design and test related problems may not prove as fruitful
as was once thought."
For many years, the dominant fault model in automatic test pattern
gen eration (ATPG) for digital integrated circuits has been the
stuck-at fault model. The static nature of stuck-at fault testing
when compared to the extremely dynamic nature of integrated circuit
(IC) technology has caused many to question whether or not stuck-at
fault based testing is still viable. Attempts at answering this
question have not been wholly satisfying due to a lack of true
quantification, statistical significance, and/or high computational
expense. In this monograph we introduce a methodology to address
the ques tion in a manner which circumvents the drawbacks of
previous approaches. The method is based on symbolic Boolean
functional analyses using Or dered Binary Decision Diagrams
(OBDDs). OBDDs have been conjectured to be an attractive
representation form for Boolean functions, although cases ex ist
for which their complexity is guaranteed to grow exponentially with
input cardinality. Classes of Boolean functions which exploit the
efficiencies inherent in OBDDs to a very great extent are examined
in Chapter 7. Exact equa tions giving their OBDD sizes are derived,
whereas until very recently only size bounds have been available.
These size equations suggest that straight forward applications of
OBDDs to design and test related problems may not prove as fruitful
as was once thought."
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