owards a unified framework for holistic study and analysis of discrete events systems

Abstract

Simulation-based and Formal Methods (FM) approaches are often used to provide solutions to complex problems through analysis of system properties. Significant theoretical advancements have been made over the years in the area of developing formalisms and solution algorithms for system-based computational science; however, most existing system development environments are dedicated to certain analysis methodologies thereby making it (almost) a necessity to always build separate models of the same system for different analyses. Therefore, exhaustive analysis of systems often require more modeling efforts and skills since no single method is sufficient to investigate all aspects of a system. In this research, we propose a blueprint for developing an extensible multi-objective framework to harness the synergy of disparate approaches for holistic analysis of Discrete Events Systems (DES). The proposed methodology relies on model-driven development (MDD) techniques to derive models for disparate analysis objectives from a unified reference model at the kernel of the framework.