Implementing dynamic flowgraph methodology models with logic programs

Abstract

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.

Incorporating software failure in risk analysis – Part 1: Software functional failure mode classification

“…Some risk-analysis approaches have been introduced to cover the risk contribution of software. Examples are software failure mode and effects analysis (FMEA) [14][15][16][17][18][19][20]), dynamic-flowgraph methodology (DFM) [21][22][23][24], or simulations with failure mode injection [25][26][27]). The current methods make only limited use of available information and the context of use (i.e., the interaction with other software, hardware, or human operators).…”