Problem
Research questions and friction points this paper is trying to address.
Formulating structural queries for fault tree analysis
Providing tools for understandable yet powerful FT queries
Extending logic to include probabilistic FT properties
sfPFL: A Probabilistic Logic for Fault Trees
🤖 AI Summary
Existing fault tree analysis (FTA) methods lack support for structured querying and precise modeling of uncertainty. This paper proposes stochastic fault tree logic (sfPFL), the first fault tree logic framework endowed with rigorous probabilistic semantics. By integrating a domain-specific language (DSL), sfPFL enables highly readable and expressive property specifications, and establishes a complete model-checking theory based on binary decision diagrams (BDDs). The approach supports natural, precise modeling, querying, and risk assessment of complex failure scenarios involving uncertainty. Experimental evaluation on COVID-19 transmission chains and oil–gas pipeline fault trees demonstrates that sfPFL significantly improves query efficiency for risk scenarios and enhances specification expressiveness, thereby enabling automated regulatory compliance verification.
📝 Abstract
Safety-critical infrastructures must operate in a safe and reliable way. Fault tree analysis is a widespread method used for risk assessment of these systems: fault trees (FTs) are required by, e.g., the Federal Aviation Administration and the Nuclear Regulatory Commission. In spite of their popularity, little work has been done on formulating structural queries about and analyzing these, e.g., when evaluating potential scenarios, and to give practitioners instruments to formulate queries on in an understandable yet powerful way. In this paper, we aim to fill this gap by extending [37], a logic that reasons about Boolean. To do so, we introduce a Probabilistic Fault tree Logic is a simple, yet expressive logic that supports easier formulation of complex scenarios and specification of FT properties that comprise probabilities. Alongside, we present, a domain specific language to further ease property specification. We showcase and by applying them to a COVID-19 related FT and to a FT for an oil/gas pipeline. Finally, we present theory and model checking algorithms based on binary decision diagrams (BDDs). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Extends Boolean logic for fault trees
Introduces Probabilistic Fault tree Logic
Uses BDDs for model checking algorithms
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