AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering

Alessandra Bagnato; Antonio Cicchetti; Luca Berardinelli; Hugo Bruneliere; R. Eramo

AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering

Alessandra Bagnato, Antonio Cicchetti, Luca Berardinelli, Hugo Bruneliere, R. Eramo

Institute of Business Informatics - Software Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

he paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in Cyber-Physical Systems (CPS). To this end, the project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable and reliable CPSs. This paper introduces the AIDOaRt project, its overall objectives, and used requirement engineering methodology. Based on that, it also focuses on describing the current plan regarding a set of tools intended to cover the modelbased capabilities requirements from the project.

Original language	English
Title of host publication	DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium.
Number of pages	5
Publication status	Published - Dec 2023

Fields of science

102006 Computer supported cooperative work (CSCW)
102015 Information systems
102016 IT security
102020 Medical informatics
102022 Software development
102027 Web engineering
102034 Cyber-physical systems
509026 Digitalisation research
502032 Quality management
502050 Business informatics
503015 Subject didactics of technical sciences

JKU Focus areas

Digital Transformation

Cite this

Bagnato, A., Cicchetti, A., Berardinelli, L., Bruneliere, H., & Eramo, R. (2023). AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering. In DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium.

Bagnato, Alessandra ; Cicchetti, Antonio ; Berardinelli, Luca et al. / AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering. DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium.. 2023.

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abstract = "he paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in Cyber-Physical Systems (CPS). To this end, the project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable and reliable CPSs. This paper introduces the AIDOaRt project, its overall objectives, and used requirement engineering methodology. Based on that, it also focuses on describing the current plan regarding a set of tools intended to cover the modelbased capabilities requirements from the project.",

author = "Alessandra Bagnato and Antonio Cicchetti and Luca Berardinelli and Hugo Bruneliere and R. Eramo",

year = "2023",

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language = "English",

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Bagnato, A, Cicchetti, A, Berardinelli, L, Bruneliere, H & Eramo, R 2023, AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering. in DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium..

AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering. / Bagnato, Alessandra; Cicchetti, Antonio; Berardinelli, Luca et al.
DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium.. 2023.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

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T1 - AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering

AU - Bagnato, Alessandra

AU - Cicchetti, Antonio

AU - Berardinelli, Luca

AU - Bruneliere, Hugo

AU - Eramo, R.

PY - 2023/12

Y1 - 2023/12

N2 - he paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in Cyber-Physical Systems (CPS). To this end, the project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable and reliable CPSs. This paper introduces the AIDOaRt project, its overall objectives, and used requirement engineering methodology. Based on that, it also focuses on describing the current plan regarding a set of tools intended to cover the modelbased capabilities requirements from the project.

AB - he paper presents the AIDOaRT project, a 3 years long H2020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in Cyber-Physical Systems (CPS). To this end, the project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable and reliable CPSs. This paper introduces the AIDOaRt project, its overall objectives, and used requirement engineering methodology. Based on that, it also focuses on describing the current plan regarding a set of tools intended to cover the modelbased capabilities requirements from the project.

UR - https://hal.archives-ouvertes.fr/hal-03719971/file/AIDOaRT_DeCPS_Paper_AuthorsVersion.pdf

M3 - Conference proceedings

BT - DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium.

ER -

Bagnato A, Cicchetti A, Berardinelli L, Bruneliere H, Eramo R. AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering. In DeCPS 2022, co-located with the 26th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2022), June 17, 2022, Ghent, Belgium.. 2023

AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering

Abstract

Fields of science

JKU Focus areas

Other files and links

AIDOaRt: AI-augmented DevOps, a model-based framework for continuous development At RunTime for CPSs

Cite this

AI-augmented Model-Based Capabilities in the AIDOaRt Project: Continuous Development of Cyber-Physical Systems. Challenges and New Approaches for Dependable and Cyber-Physical System Engineering

Abstract

Fields of science

JKU Focus areas

Other files and links

Projects

AIDOaRt: AI-augmented DevOps, a model-based framework for continuous development At RunTime for CPSs

Cite this