Conference Romina Eramo, Vittoriano Muttillo, Luca Berardinelli, Hugo Bruneliere, Abel Gómez, Alessandra Bagnato, Andrey Sadovykh, Antonio Cicchetti AIDOaRt: AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems 2021 24th Euromicro Conference on Digital System Design (DSD), IEEE, 2021, ISBN: 978-1-6654-2703-6. Abstract | Links | BibTeX | Tags: AIOps, Artificial Inteligence (AI), Continuous System Engineering, Cyber-Physical Systems (CPS), DevOps @conference{Eramo:DSD:2021,
title = {AIDOaRt: AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems},
author = { Romina Eramo and Vittoriano Muttillo and Luca Berardinelli and Hugo Bruneliere and Abel G\'{o}mez and Alessandra Bagnato and Andrey Sadovykh and Antonio Cicchetti},
doi = {10.1109/DSD53832.2021.00053},
isbn = {978-1-6654-2703-6},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
booktitle = {2021 24th Euromicro Conference on Digital System Design (DSD)},
pages = {303-310},
publisher = {IEEE},
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.},
keywords = {AIOps, Artificial Inteligence (AI), Continuous System Engineering, Cyber-Physical Systems (CPS), DevOps},
pubstate = {published},
tppubtype = {conference}
}
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. |