## 1 Introduction
(2019), to overcome the limitations of traditional reliability allocation methods, such as the weak ability to express and process fuzzy information and the unreasonable use of data, Rough Set Theory (RST) and proportional risk model are introduced into the reliability allocation process for the first time, which improves the relevance and accuracy of reliability allocation. [PERSON] et al. (2019) introduced fuzzy set theory into the comprehensive allocation method to fuzzy-rate criteria with high subjective dependence. The subjective quantification problem in traditional reliability allocation methods is avoided by fuzzy ratings for failure severity and failure incidence. [PERSON] et al. (2019) conducted a hybrid design study consisting of individual nature-inspired algorithms to address the reliability redundancy allocation problem. The results of the study demonstrate the efficiency of the hybrid scheme, supporting the hypothesis that hybridization can improve the performance of optimization methods. [PERSON] et al. (2020, 2019) analyzed operational strategies, technology usage, renewable energy, alternative fuels, and energy management systems to improve energy efficiency and environmental performance of ports and terminals. In another study, a mixed-integer linear programming model was proposed to address the comprehensive operational planning and energy management issues of smart grid seaports, considering uncertain renewable energy generation. The above research provides a reliable theoretical basis for achieving information exchange between ships and ports. In addition, we proposed a decision support system (DSS) in 2024 to collaborate with en route ports in service, optimizing the cargo composition and loading plans of shipping companies' container ships (2020). Numerical experiments indicate that the proposed DSS can return high-quality solutions for all ship sizes, cargo contents, and routes within a reasonable solution time, supporting the circular economy principle in the maritime field. This study is of great significance in exploring the relationship and impact between system reliability and ship stability parameters. Architecture Analysis and Design Language (AADL) is a language for modeling and analysis of real-time embedded systems [23], which has the advantages of openness and extensibility [24]. AADL can support the description of different levels of components and subsystems, and the reuse of system patterns, which allows for a more comprehensive description of the characteristics and behaviors of the system [25]. In addition, system analysis and validation can be conducted through model checking and simulation, which can more quickly and accurately identify problems and defects in the system [26]. AADL, as an open modeling language, can be integrated with other modeling languages and tools to extend its modeling and analysis capability, making it more suitable for different fields and application scenarios [27]. In the 1960s, the GO (Goal Oriented) method for system reliability analysis was proposed by Kaman USA, Inc., aiming to facilitate the development of weapons and for determining the reliability of a system [28]. Subsequently, the Electric Power Research Institute (EPRI) of the United States, in cooperation with them, refined the GO method [29; 30] and applied it in safety inspections and analyzing the reliability of several nuclear power plants. In the late 1980s, the Naval Research Institute of Japan proposed a new reliability analysis method, GO-FLOW [31]. This method not only satisfies the system with time series and phase mission requirements but also better guides the reliability analysis of the system, bringing new thinking and new methods for reliability analysis and system application [32; 33]. In this study, the problems of current common ship electronic information system reliability modeling, allocation, and analysis methods are discussed and studied in detail.