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CAE stands for Claims Arguments Evidence, and is a framework for reasoning and communicating. The initial application was in reasoning to explore the safety and trustworthiness of systems as captured in safety and assurance cases. However, CAE is more broadly applicable to reasoning about complex systems where confidence comes from challenging and developing understanding across disparate groups of people and disciplines. CAE can be used throughout the lifecycle, from brainstorming and optioneering to detailed rigorous explanations. What constitutes a good application of CAE depends on the decision being explored, the stakeholders and the stage of the project.

This website aims to inform professionals on the concepts and application of CAE, and provide signposting to and downloads of relevant resources. Assurance cases provide a means to justify and challenge the trustworthiness of complex systems, with CAE focusing on the safety, security and system aspects. We provide background information and resources about CAE and assurance cases from a variety of application areas, particularly from the Nuclear Industry, Medical, Civil Aviation and Defence domains.

We have decided to launch the website now with what we judge is enough content to be useful. We are keen to hear from you about whether you do indeed find it useful and what additional things you would like to see on the site. Please consider registering to get CAE related news and updates. We would like the website to become a community effort, so please get in touch (cae@adelard.com) with any offers of resources, additions, correction and the like.

The website, created and curated by Adelard LLP, recognises the support from academics and researchers at City, University of London and the Research Institute in Trustworthy Interconnected Cyber Physical Systems (RITICS) in the UK.

If you are familiar with CAE and the concepts, please take time to see how we now define them and review the use of CAE Building Blocks.  These allow us to distinguish between deductive and inductive reasoning, and between those aspects we can gain confidence from verifying models and those we need to validate with respect to the real-world. We also provide some information on  tools for cases.

 

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