An Abstract Language for Specifying Markov Reliability Models

In principle, Markov models can be used to describe the reliability of virtually any fault-tolerant system. However, the process of delineating all of the states and transitions in a model of a complex system can be devastatingly tedious and error-prone. This paper presents a new approach to this problem by using an abstract model-definition language. The language essentially defines a set of rules which are used to generate the Markov model automatically. These rules correspond to the basic concepts used to create models of fault-tolerant systems. A small number of statements in the language can be used to describe a very large model. A variation in the system (such as in the number of initial spares) can be accomplished by changing only one line in the model definition, although such a change represents a large increase in the size of the Markov model. This high-level language is described in a non-formal manner and illustrated by several examples. A computer program has been developed which translates the abstract language described in this paper into the input language for the SURE (Semi-Markov Unreliability Range Evaluator) program. The program has been named ASSIST (Abstract Semi-Markov Specification Interface to the SURE Tool). It is written in Pascal and runs on a VAX 11/750 in the NASA AIRLAB Facility.