## 2 State of the Art  
The extensive body of literature on the topic underscores the key role of reliability and risk modeling in interconnected infrastructures. This review commences with a thorough assessment of both foundational texts and the most relevant recent studies on the subject. In [2], the authors undertake an exhaustive survey of more than 150 papers pertaining to Fault Tree Analysis (FTA), thereby rendering an in-depth insight into the state-of-the-art methodologies of FTA. This exploration not only covers the traditional aspects of the Fault Tree (FT), but also discusses its several extensions, including Dynamic Fault Tree (DFT), Repairable Fault Tree (RFT), and Extended Fault Tree (EFT). Reference [3] discusses the mathematical framework behind the optimal allocation and planning of maintenance personnel, casting maintenance optimization as a multi-faceted optimization problem. In another significant contribution [4], a broad spectrum of reliability and risk modeling techniques is introduced. These range from the Conventional Fault Tree (CFT), Event Tree (ET), and Binary Decision Diagram (BDD) to more nuanced methods like Petri Nets (PN), Markov Modeling (MM), and Attack Tree (AT), designed to identify and mitigate the latent risks which are characteristic for Cyber-Physical Systems (CPS). In line with DFT, a chapter in [5] analyzes the methodology, reviewing popular techniques including Markov chains and Bayesian networks. Systematic review [6] covers Reliability, Availability, Maintainability, and Safety/Security (RAMS) analysis of Critical Infrastructure (CI) papers. Altogether, 1500 papers which cover the RAMS topic published between 2011 and 2020 are analyzed. The target applications include grid stations, cyber-physical systems, cloud computing, software-defined networks, industrial control systems, and Supervisory Control And Data Acquisition (SCADA) systems. In [7], AT are categorized into two distinct dimensions: (i) proper trees versus directed AG, and (ii) static gates versus dynamic gates. On another front, in [8], a comprehensive overview of reliability modeling in CPS is delivered. This includes highlighting the intricacies associated with reliability and fault modeling across the three core components of CPS: hardware, software, and humans. Furthermore, the authors analyze challenges arising from the integration of these components to offer a holistic approach to CPS reliability modeling. Innovative paper [9] presents a methodology that focuses on deriving repairable multi-state FT from time series fault data. This method is adept at analyzing non-exponential distributions of both reliability and maintainability, and it proves instrumental in predicting the system's future reliability along with detailing the FT structure. Lastly, in [10], attention is centered on the generation of DFT for systems that incorporate redundancies. These redundancies, commonplace in safety-critical systems, serve the primary purpose of enhancing system reliability. The authors' objective in this paper is twofold: first, to introduce a redundancy profile, and second, to pave the way for the automatic generation of DFT based on system models. In recent years, a focus has been placed on software tools tailored for the reliability analysis of systems. The 2017 report on open-source FTA tools, as mentioned in [11], highlighted several tools. Their findings, updated to reflect the current status, list the following tools:  
* **OpenFTA** (Open-source): OpenFTA, an FTA tool, aids in comprehending and applying FTA, a method in safety engineering for qualitative and quantitative evaluation of CI system reliability and safety. However, having not been updated for over a decade, its relevance in contemporary applications might be questionable. * **OpenAltaRica** (Restricted free access): OpenAltaRica focuses on risk analysis of intricate systems using the AltaRica language, a high-tier language crafted for the RAMS analysis of systems.