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 112020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AIaugmented 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 automate 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.
AIDOaRt: AI -augmented Automation for DevOps, a Model -based Framework for Continuous Development in Cyber-Physical Systems
Eramo, R;Muttillo, V;
2021-01-01
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 112020-ECSEL European project involving 32 organizations, grouped in clusters from 7 different countries, focusing on AIaugmented 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 automate 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.