A BDD-based algorithm for computation of exact fault detection probabilities

An accurate probabilistic model for error detection

“…In Table 2, we compare LIFE-BN fault modeling with the performance of approaches based on the Binary Decision Diagram (BDD) model, as reported by Krieger et al [4] for these same circuits. They reported results using four type of fault partitioning.…”

“…Gates with more than two inputs are reduced to two-input gates by introducing additional dummy nodes, without changing the logic structure and accuracy. First, we determine the hard faults using ½¼¾ random input vectors [4]. Faults that are not detected by these vectors are hard faults.…”

“…Existing algorithms for computation of exact fault detection probabilities, mostly based on Binary Decision Diagrams [4] do not scale well, in terms of time and space requirements, with circuit size. They usually require various heuristicbased approximations of the pure model.…”

“…PLATO (Probabilistic Logic Analyzing Tool) [4] is another tool to compute exact fault detection probabilities using reduced ordered binary decision diagrams (ROBDD)s. Space requirement for constructing the ROBDD of large circuits is very large. Shannon decomposition and divide-and-conquer strategies are used to reduce large circuits into small sub-circuits.…”

OBDD-based optimization of input probabilities for weighted random pattern generation

“…It turns out in the following that this leads to a significant improvement for weight optimization. Of course, a crucial point of the whole concept is the computation of the exact fault detection probabilities: I Recently, a method based upon Binary Decision Diagrams [5] (OBDD) was presented [14]. For the first time, it allows the exact computation of fault detection probabilities even for larger circuits.…”