AIDOaRt: AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems - Archive ouverte HAL Access content directly
Journal Articles Microprocessors and Microsystems: Embedded Hardware Design Year : 2022

AIDOaRt: AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems

Vittoriano Muttillo
  • Function : Author
  • PersonId : 1105341
Romina Eramo
  • Function : Author
  • PersonId : 1077806
Abel Gomez
  • Function : Author
  • PersonId : 1105343
Alessandra Bagnato​
  • Function : Author
  • PersonId : 975445
Andrey Sadovykh
Antonio Cicchetti
  • Function : Author
  • PersonId : 994804

Abstract

The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modelling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will 1) enable the dynamic observation and analysis of system data collected at both runtime and design time and 2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans.
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Dates and versions

hal-03769797 , version 1 (05-09-2022)

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Hugo Bruneliere, Vittoriano Muttillo, Romina Eramo, Luca Berardinelli, Abel Gomez, et al.. AIDOaRt: AI-augmented Automation for DevOps, a Model-based Framework for Continuous Development in Cyber-Physical Systems. Microprocessors and Microsystems: Embedded Hardware Design , 2022, 94, pp.104672. ⟨10.1016/j.micpro.2022.104672⟩. ⟨hal-03769797⟩
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