Engineering Framework for the Generation and Integration of Digital Dependability Identities

Regan, Gilbert and McCaffery, Fergal and Longo, Simone and Reich, Jan and Schneider, Daniel and Sorokos, Ioannis and Guo, Joe and Zeller, Marc and Wei, Ran and Kelly, Tim Engineering Framework for the Generation and Integration of Digital Dependability Identities. DEIS Project. (Submitted)

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Cyber-Physical Systems (CPS) provide enormous potential for new types of applications, services and business models in any embedded systems domain, such as automotive, rail, healthcare or home automation. Overall, we anticipate a future of heavily interconnected, distributed, heterogeneous and intelligent systems, which are bound to have a significant economical and societal impact in the years to come. However, several challenges need to be tackled before the full potential of CPS can be unlocked. One core challenge is to ensure the trustworthiness and dependability of single and composite systems, as established approaches and standards were designed with closed standalone systems in mind, thus building on a complete understanding and analysability of a system and its relevant environment. As this is no longer a given, we urgently require new types of approaches that do not (solely) rely on this basic assumption (now rendered void). A general solution concept involves shifting parts of the assurance activities into runtime, where unknowns and uncertainties can be resolved dynamically. To this end, it is necessary to equip the constituent systems with dedicated and adequate modularised and formalised dependability information. The key innovation that is the aim of DEIS is the corresponding concept of a Digital Dependability Identity (DDI). A DDI contains all the information that uniquely describes the dependability characteristics of a CPS or CPS component. DDIs are synthesised at development time and are the basis for the (semi-)automated integration of components into systems during development, as well as for the fully automated dynamic integration of systems into systems of systems in the field. In this document we build upon the initial version of the ODE meta-model and present version 2 of the model, which now includes a new security package. The main goal of this document is to specify the algorithms needed to provide adequate engineering support for the generation and integration of DDIs. With this goal in mind, tool transformations are specified so that DDI’s can be generated from information already stored in existing tools. Additionally, this document demonstrates how tools can be used to generate DDI’s in a semi-automated way, and how the integration of DDI into existing systems can be achieved through the use of supported tools in a semi-automated way, thus increasing efficiency as well as the confidence in the system’s dependability. For the integration of DDIs, the information contained in DDIs must be transformed back into an appropriate (ODE-compliant) format that can be used in the tool chain used by the integrator. Finally, verification of the utility of DDI is demonstrated through presenting how DDIs support a number of DEIS use cases and engineering stories, and how DDIs can be used in applications that must comply with the new General Data Protection Regulations (GDPR). DEIS aims at providing comprehensive tool support for DDI, covering the supported/semi-automated synthesis of DDI as well as the (semi-)automated integration at development time. Moreover, it is our aim to support multi-tool scenarios, where DDI are exchanged and evolved among different development teams and tools.

Item Type: Article
Subjects: Computer Science
Computer Science > Computer Software
Research Centres: Regulated Software Research Centre
Depositing User: Sean McGreal
Date Deposited: 21 Jan 2020 10:06
Last Modified: 21 Jan 2020 10:06
License: Creative Commons: Attribution-Noncommercial-Share Alike 4.0

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