Hardware Reference
In-Depth Information
2.4.1
Logic Diagnosis Techniques
Diagnosis of bridging faults by using information from single SA faults was com-
mon in the past, since processing SA faults is computationally simpler than process-
ing bridging faults, both in terms of fault list size and fault simulation complexity.
Different logic diagnosis methodologies have been developed using fault dictio-
naries and fault simulation. In the fault dictionary method ( Millman et al. 1990 ;
Chakravarty and Gong 1993 , 1995 ; Chess et al. 1995 ; Aitken and Maxwell 1995 ;
Lavo et al. 1998 ), the faulty response of each considered bridging fault is stored
for every test pattern. The diagnosis process is carried out comparing the output
response of the failing device to the information contained in the fault dictionary
of bridges. In the works by Chakravarty and Gong ( 1993 , 1995 ) the initialization
graphs are used for generating the initial set of bridging fault candidates. Subse-
quently, a set of pruning rules are considered to reduce the candidates set. The first
work Chakravarty and Gong ( 1993 ) is based on the wired-AND and the wired-OR
bridging fault model, whereas the second work ( Chakravarty and Gong 1995 )is
based on the voting model. Other works ( Millman et al. 1990 ; Chess et al. 1995 ;
Aitken and Maxwell 1995 ) took benefit from composite signatures. A composite
signature (Millman et al. 1990) is the bridge fault signature resulting from the union
of the four stuck-at fault signatures associated with the bridged nodes. The main im-
provement in the work by Chess et al. ( 1995 ) related to previous work in Millman
et al. ( 1990 ) is the restriction of the number of faults under consideration, which in-
creases the efficiency of the methodology. This is achieved by eliminating from the
composite signature entries that cannot be used to detect the bridging fault and also
defining the set of vectors which should detect a particular bridge. In Aitken and
Maxwell ( 1995 ), quality measurements were defined to create a ranking criterion
for bridging faults diagnosis. These quality measurements were subsequently used
for other works and even applied to other fault models. The criterion is based on
the comparison between the results obtained on the tester and the prediction of the
bridging fault model. The part of the tester results which is also included in the fault
model prediction is called Intersection (see Fig. 2.20 ) . Failing vectors predicted by
the fault model which have not failed on the tester are called Mispredictions. Vectors
Tester Result
Fault Model Prediction
Non-prediction
Intersection
Misprediction
Fig. 2.20 Matching
algorithm ( Aitken and
Maxwell 1995 )
 
 
 
 
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