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AIDOaRt: AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems
University of L’Aquila, L’Aquila, Italy.
University of L’Aquila, L’Aquila, Italy.
Johannes Kepler University, Linz, Austria.
IMT Atlantique LS2N (UMR CNRS 6004) Nantes, France.
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2021 (English)In: 2021 24th Euromicro Conference on Digital System Design (DSD), 2021, p. 303-310Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2021. p. 303-310
Keywords [en]
Automation;Europe;Organizations;Cyber-physical systems;Continuous time systems;Software;Artificial intelligence;Continuous System Engineering;DevOps;AIOPS;Software engineering;Scientific computing;Simulation and Modelling Tools;Cyber-Physical Systems;Artificial Intelligence
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-56440DOI: 10.1109/DSD53832.2021.00053ISI: 000728394500044Scopus ID: 2-s2.0-85119884136ISBN: 978-1-6654-2703-6 (electronic)OAI: oai:DiVA.org:mdh-56440DiVA, id: diva2:1609988
Conference
2021 24th Euromicro Conference on Digital System Design (DSD), 1-3 Sept. 2021
Available from: 2021-11-09 Created: 2021-11-09 Last updated: 2022-03-18Bibliographically approved

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Cicchetti, Antonio

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