ABSTRACT

Computer systems are prone to failures. Failures are caused by faults that occur in a system. As faults are unknown and cannot be measured, they produce error messages on their detection. The approach presented here is to create a Hidden Markov Model from the given data of error sequence and describes two techniques, Gaines algorithm and Minimum message length estimator to obtain a most appropriate Hidden Markov Model with optimized number of states. For a given sequence it is shown that both the two techniques ensure same optimal Hidden Markov Model with maximum probability.