| 1. |
- Afzal, Wasif, et al.
(författare)
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The MegaM@Rt2 ECSEL Project : MegaModelling at Runtime — Scalable Model-Based Framework for Continuous Development and Runtime Validation of Complex Systems
- 2017
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Ingår i: The 2017 Euromicro Conference on Digital System Design DSD'17. - 9781538621462
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Konferensbidrag (refereegranskat)abstract
- A major challenge for the European electronic industry is to enhance productivity while reducing costs and ensuring quality in development, integration and maintenance. Model-Driven Engineering (MDE) principles and techniques have already shown promising capabilities but still need to scale to support real-world scenarios implied by the full deployment and use of complex electronic components and systems. Moreover, maintaining efficient traceability, integration and communication between two fundamental system life-time phases (design time and runtime) is another challenge facing scalability of MDE. This paper presents an overview of the ECSEL project entitled "MegaModelling at runtime -- Scalable model-based framework for continuous development and runtime validation of complex systems" (MegaM@Rt2), whose aim is to address the above mentioned challenges facing MDE. Driven by both large and small industrial enterprises, with the support of research partners and technology providers, MegaM@Rt2 aims to deliver a framework of tools and methods for: 1) system engineering/design & continuous development, 2) related runtime analysis and 3) global model & traceability management, respectively. The diverse industrial use cases (covering domains such as aeronautics, railway, construction and telecommunications) will integrate and apply such a framework that shall demonstrate the validation of the MegaM@Rt2 solution.
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| 2. |
- Eramo, Romina, et al.
(författare)
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AIDOaRt : AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems
- 2021
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Ingår i: 2021 24th Euromicro Conference on Digital System Design (DSD). - 9781665427036 ; , s. 303-310
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Konferensbidrag (refereegranskat)abstract
- With the emergence of Cyber-Physical Systems (CPS), the increasing complexity in development and operation demands for an efficient engineering process. In the recent years DevOps promotes closer continuous integration of system development and its operational deployment perspectives. In this context, the use of Artificial Intelligence (AI) is beneficial to improve the system design and integration activities, however, it is still limited despite its high potential. AIDOaRT is a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modelling, coding, testing, monitoring and continuous development of Cyber-Physical Systems (CPS). The project proposes to apply Model-Driven Engineering (MDE) principles and techniques to provide a framework offering proper AI-enhanced methods and related tooling for building trustable CPSs. The framework is intended to work within the DevOps practices combining software development and information technology (IT) operations. In this regard, the project points at enabling AI for IT operations (AIOps) to auto-mate decision making process and complete system development tasks. This paper presents an overview of the project with the aim to discuss context, objectives and the proposed approach.
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