The authors present two methods for computing the fault detection probabilities in combinational networks. The methods provide a deeper insight into the effects of signal correlations caused by multiple fan-out reconvergencies and can be used in testability analysis to predict the fault coverage of pseudorandom patterns. The performances of these algorithms have been tested on significant benchmarks and compare favorably with those of previous procedures.>

We describe a new approach for technology mapping of electri-

An investigation of the properties of multiple input shift registers for signature analysis is presented. The assumption of independent errors at the register inputs has been used to model the register behavior as a Markov process whose equations have been solved to obtain the exact dependence of aliasing probabilities as a function of test length, input error probabilities, and feedback structure. Some unique featured of maximum-length registers are proven. Accurate simplified expressions of aliasing probability are derived for use as tools in the evaluation of the coverage.>

Two methods for the calculation of fault detection probabilities in combinational networks are presented. These methods provide a better accuracy than existing algorithms and a deeper insight into the effects of first order correlations to multiple fan-out reconvergencies. These techniques have been applied to standard benchmarks as well as to a few commercial circuits and have shown to provide a significant improvement compared with existing methods with minimal drawbacks in terms of required computing resources.>