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      Modular Assurance of Complex Systems Using Contract-Based Design Principles

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          Abstract

          A growing number of safety-critical industries agree that building confidence in complex systems can be achieved through evidence and structured argumentation framed in assurance cases. Nevertheless, assurance cases can easily become too rigorous and difficult to develop and maintain when applied to complex systems. Therefore, we propose to use contract-based development (CBD), a method to manage complexity originally developed in computer science, to simplify assurance cases by modularizing them. This paper will not only summarize relevant previous work such as constructing consistent modular assurance cases using CBD, but more importantly also propose a novel approach to integrate CBD with the argumentation in assurance case modules. This approach will allow interdisciplinary subject-matter and domain experts to build assurance cases together without even knowing about CBD. This helps subject matter experts outside of computer science to reap benefits from CBD and helps with interdisciplinary co-development of assurance cases that cover all the required fields. This paper motivates four rules of thumb aimed to help practitioners developing high-quality modular assurance cases. It also explains how modularization of assurance is an enabler for multi-concern assurance that accounts for the inter-dependency of different concerns such as safety, security and performance.

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          Author and article information

          Journal
          20 February 2024
          Article
          2402.12804
          4cfd710a-e474-4a02-9cb5-c378d3a5bdb3

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

          History
          Custom metadata
          14 pages, 6 figures, manuscript submitted to the 43rd International Conference in Computer Safety, Reliability, and Security (SAFECOMP 2024)
          cs.LO cs.SE

          Software engineering,Theoretical computer science
          Software engineering, Theoretical computer science

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