Implementing dynamic flowgraph methodology models with logic programs

The dynamic flowgraph methodology is a promising way to find the prime implicants of a top event for a dynamic system possibly containing digital subsystems. This article demonstrates how to express dynamic flowgraph methodology models as logic programs, and top events as queries to those programs, in a natural and comprehensible way. Computation of the logic program lists the prime implicants of a top event in the system. We also present and implement an algorithm for computing the probability of the top event from its prime implicants. Together, computation of prime implicants and calculation of top event probability from these constitute a complete way of finding a system's failure probability. Logic programs, implemented in this article in the leading logic programming language Prolog, enable rapid prototyping of dynamic flowgraph methodology models. The logic programming framework introduced here could also be utilized in teaching dynamic flowgraph methodology in risk analysis courses.