TY - JOUR
T1 - Fault Coverage and Test Length Estimation for Random Pattern Testing
AU - Majumdar, Amitava
AU - Vrudhula, Sarma B.K.
N1 - Funding Information:
Manuscript received November 30, 1993; revised April 21, 1994. This work was supported in part by NSF award MIP-9111206, by a grant from DARPA monitored by the FBI under Contract JFBI 90092. A. Majumdar is with Crosscheck Technology Inc., San Jose, CA 95134 USA. S. B. K. Vrudhula is with the Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ 85721 USA. IEEE Log Number 9407132.
PY - 1995/2
Y1 - 1995/2
N2 - Fault coverage and test length estimation in circuits under random test is the subject of this paper. Testing by a sequence of random input patterns is viewed as sequential sampling of faults from a given fault universe. Based on this model, the probability mass function (pmf) of fault coverage and expressions for all its moments are derived. This provides a means for computing estimates of fault coverage as well as determining the accuracy of the estimates. Test length, viewed as waiting time on fault coverage, is analyzed next. We derive expressions for its pmf and its probability generating function (pgf). This allows computation of all the higher order moments. In particular, expressions for mean and variance of test length for any specified fault coverage are derived. This is a considerable enhancement of the state of the art in techniques for predicting test length as a function of fault coverage. It is shown that any moment of test length requires knowledge of all the moments of fault coverage, and hence, its pmf. For this reason, expressions for approximating its expected value and variance, for user specified error bounds, are also given. A methodology based on these results is outlined. Experiments carried out on several circuits demonstrate that this technique is capable of providing excellent predictions of test length. Furthermore it is shown, as with fault coverage prediction, that estimates of variances can be used to bound average test length quite effectively.
AB - Fault coverage and test length estimation in circuits under random test is the subject of this paper. Testing by a sequence of random input patterns is viewed as sequential sampling of faults from a given fault universe. Based on this model, the probability mass function (pmf) of fault coverage and expressions for all its moments are derived. This provides a means for computing estimates of fault coverage as well as determining the accuracy of the estimates. Test length, viewed as waiting time on fault coverage, is analyzed next. We derive expressions for its pmf and its probability generating function (pgf). This allows computation of all the higher order moments. In particular, expressions for mean and variance of test length for any specified fault coverage are derived. This is a considerable enhancement of the state of the art in techniques for predicting test length as a function of fault coverage. It is shown that any moment of test length requires knowledge of all the moments of fault coverage, and hence, its pmf. For this reason, expressions for approximating its expected value and variance, for user specified error bounds, are also given. A methodology based on these results is outlined. Experiments carried out on several circuits demonstrate that this technique is capable of providing excellent predictions of test length. Furthermore it is shown, as with fault coverage prediction, that estimates of variances can be used to bound average test length quite effectively.
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U2 - 10.1109/12.364535
DO - 10.1109/12.364535
M3 - Article
AN - SCOPUS:0029254427
SN - 0018-9340
VL - 44
SP - 234
EP - 247
JO - IEEE Transactions on Computers
JF - IEEE Transactions on Computers
IS - 2
ER -