# Reliability Analysis of C\({}^{4}\)ISR Systems Based on Goal-Oriented Methodology
## 1 Introduction  
Command and control systems (C\({}^{4}\)ISR systems), integrated by both hardware and software, are the core element of battlefield command and dispatch operations, which are designed to reliably and error-freely distribute commands to all stakeholders under the complex, variable and unpredictable battlefield conditions during wartime [1]. Therefore, the reliability of such systems is always one of the core performance features that need to be investigated. However, two characteristics of C\({}^{4}\)ISR systems, that are, complicated configurations of systems and large-scale information involved, introduce chaos to the reliable operation of these systems, especially to their failure mechanism identification, reliability analysis, and availability improvement [1, 2]. Failure frequency of C\({}^{4}\)ISR systems is high under the real battlefield circumstance according to the failure information already mentioned and which reduces significantly the reliability, availability, failure-free operation time of C\({}^{4}\)ISR systems [3]. To this end, a thorough and comprehensive reliability analysis of C\({}^{4}\)ISR systems is mandatory before its delivery and installation to end-users. System reliability analysis is to discover and determine the risky factors that may lead to malfunctions during the design and actual operation of systems so that to improve the system's reliability by preventing the occurrence of critical failures. However, unlike mechanical, electrical, and software systems that consist of either hardware or software systems, C\({}^{4}\)ISR systems were composed of both, which introduces additional difficulties to the reliability analysis of such systems. Each of the system's components could have a more or less complex redundant structure, but we should consider it as a whole. Consequently the system could be considered a minimal serial structure with multiple recovery capacity. The considerations regardingthe reliability modeling of combined hardware/software systems had as a starting point the Rome Laboratory's \"System and Software Reliability Assurance Notebook\" [4]. The document offers a methodology for the reliability assurance study of systems composed both from hardware and software elements, designed for estimation and prediction of its reliability. Moreover, due to the properties already mentioned above, classical reliability analysis methodologies which have been applied maturely for instance Fault Tree Analysis (FTA), Failure Mode and Effect Analysis (FMEA), and Monte Carlo (MC) method, Bayesian network (BN) and so on are not applicable for the analysis of hard-and-software integrated systems such as C\({}^{4}\)ISR systems. The Goal-Oriented (GO) method is directly connected with product structures, functions, and working principles [5]. However, due to its superior features such as easy to model dynamics in reliability modeling scholars are currently began to engage in developing and applying this method theory in various engineering cases [6; 7], especially in reliability and safety analysis of weapon and missile systems [4; 5], transportation systems [8], and power systems [6; 9]. The initial of the GO method can be traced back to 1970s, when the American Electric Power Research Institute (EPRI) highlighted the application of the GO method in the safety and availability analysis of nuclear power plants, by which the failure probability, availability, and maintainability of nuclear power plants are reached [10; 11]. The GO method also applied into risk analysis of fuel transportation [10], and post-processing files [12]. At the same time, specific GO software has been developed by companies such as Kaman Company to promote the actual implementation of such a method [12]. From the methodology development point of view, [PERSON] [13] used the GO method to evaluate the availability and risk probability of a 1.1 MW power station that composed of approximately 60 systems and 10,000 components, concluded that the GO method can simulate and analyze the entire nuclear power plant.