DocumentCode :
1245176
Title :
On testing of sequential machines using circuit decomposition and stochastic modeling
Author :
Das, Sunil R. ; Jone, Wen-Ben ; Nayak, Amiya R. ; Choi, Ian
Author_Institution :
Dept. of Electr. Eng., Ottawa Univ., Ont., Canada
Volume :
25
Issue :
3
fYear :
1995
fDate :
3/1/1995 12:00:00 AM
Firstpage :
489
Lastpage :
504
Abstract :
Test generation for sequential circuits has been a difficult task. This is due to the large search space to be considered in test pattern generation. In this paper the detection of permanent faults in sequential circuits by random testing is analyzed utilizing the circuit partitioning approach together with a continuous parameter Markov model. Given a large sequential circuit, it is partitioned into several smaller partitions using either series or parallel decomposition. For each partition with certain stuck faults specified, the original state table and its error version are derived from an analysis of the partition under fault-free and faulty conditions, respectively. A random testing strategy that uses a three-state Markov model is used for detecting permanent stuck faults. Experimentation on various sequential circuits has shown that a significant saving in testing or test generation time can be achieved if we partition the circuit and then test each of its components as opposed to testing the circuit in its original form
Keywords :
Markov processes; fault diagnosis; logic testing; sequential circuits; sequential machines; circuit decomposition; circuit partitioning; continuous parameter Markov model; decomposition; permanent stuck fault detection; random testing; sequential circuit testing; sequential machines; stochastic modeling; Circuit faults; Circuit testing; Computer science; Digital circuits; Electrical fault detection; Fault detection; Sequential analysis; Sequential circuits; Stochastic processes; Test pattern generators;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/21.364861
Filename :
364861
Link To Document :
بازگشت