Pseudorandom testing has been widely used in built-in self-testing of VLSI circuits.
Although the defect level estimation for pseudorandom testing has been performed
using sequential statical analysis, no closed form can be accomplished as complex
combinatorial enumerations are involved. In this work, a Markov model is employed to
describe the pseudorandom test behaviors. For the first time, a closed form of the defect
level equation is derived by solving the differential equation extracted from the Markov
model. The defect level equation clearly describes the relationships among defect level,
fabrication yield, the number of all input combinations, circuit detectability (in terms of
the worst single stuck-at fault), and pseudorandom test length. The Markov model is
then extended to consider all single stuck-at faults, instead of only the worst single
stuck-at fault. Results demonstrate that the defect level analysis for pseudorandom
testing by only dealing with the worst single stuck-at fault is not adequate (In fact, the
worst single stuck-at fault analysis is just a special case). A closed form of the defect
level equation is successfully derived to incorporate all single stuck-at faults into
consideration. Although our discussions are primarily based on the single struck-at fault
model, it is not difficult to extend the results to other fault types.
Defect Level Estimation for Pseudorandom Testing Using Stochastic Analysis
