A new reliability analysis method for software‐intensive systems with degradation accumulation effect based on goal oriented methodology

• Published in: Quality and reliability engineering international 2024-02, Vol.40 (1), p.236-260
• Main Authors: Yi, Xiao‐Jian, Xu, Chen‐Hao, Fang, Xiao‐Tong, Liu, Shu‐Lin
• Format: Article
• Language: English
• Subjects: Accumulation; Attenuation; Degradation; degradation accumulation effect; GO methodology; Hardware; information transmission attenuation; Markov processes; Operators (mathematics); Random variables; Reliability analysis; Software; Software reliability; software‐intensive systems; System reliability
• ISSN: 0748-8017; 1099-1638
• DOI: 10.1002/qre.3387

System reliability directly affects the realization of software‐intensive system functions, which rely on both hardware and software. The operating status of hardware and software affect each other, and the continuous accumulation of their degraded performances will accelerate the occurrence of failures. However, the interaction relationship between hardware and software is often overlooked in most current research. In this paper, a new reliability analysis method is proposed for multi‐state software‐intensive systems with degradation accumulation effect and information transmission attenuation based on goal oriented (GO) methodology. First, a new function GO operator is created, and its operation formula is derived with the aid of Markov process theory. To quantify the impact of degradation accumulation on availability, non‐negative constant and random variable critical thresholds are set for the degradation state. Then, an effective optical power loss model is established to analyze the reliability of information transmission in the presence of attenuation. Next, the reliability analysis framework for multi‐state software‐intensive system is established based on the GO method. Finally, the proposed reliability analysis method is applied to the example of meter and decameter wavelength radio heliograph to demonstrate the applicability and feasibility of our work. The proposed model provides a more accurate reflection of the system reliability under actual operating conditions.