Development of a system for identifying and analyzing systemic risks in complex technological systems based on an object-oriented approach

Abstract

The article justifies developing a system for identifying and analyzing systemic risk in complex technological environments using an object-oriented approach. The problem is driven by rising interdependencies, data volumes, and legacy integrations in high-tech sectors. The theoretical base is the Unified Foundational Ontology and the KISS principle, which sustain conceptual coherence and constrain complexity. The methodology combines user stories, architectural patterns, OOP principles (encapsulation, inheritance, polymorphism, abstraction), and safety engineering: HAZOP, FMEA, and PRA with sensitivity and uncertainty analysis. Stages include requirements elicitation, modeling, prototyping, and assessment of flows and vulnerabilities. Modularity enables threat localization, staged deployment, and integration with legacy components. Novelty lies in synthesizing ontological modeling with OO methods and in directions: e.g., object-oriented Bayesian networks (OOBN), big data analytics, expanding the Disruption Knowledge Base, and DisruptiOn Graphs for analyzing disruption scenarios and risk propagation. Practical value: guidance for designing and modernizing systems that require formal risk models. Limitations: code complexity, performance trade-offs with encapsulation, choice of granularity, risks of faulty requirement identification, and adoption barriers. No empirical measurements are reported; the work is conceptual-methodological and sets directions for further verification.