Towards Single-System Illusion in Software-Defined Vehicles -- Automated, AI-Powered Workflow

Fuente: arXiv
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Autori principali: Lebioda, Krzysztof, Vorobev, Viktor, Petrovic, Nenad, Pan, Fengjunjie, Zolfaghari, Vahid, Knoll, Alois
Natura: Preprint
Pubblicazione: 2024
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author Lebioda, Krzysztof
Vorobev, Viktor
Petrovic, Nenad
Pan, Fengjunjie
Zolfaghari, Vahid
Knoll, Alois
author_facet Lebioda, Krzysztof
Vorobev, Viktor
Petrovic, Nenad
Pan, Fengjunjie
Zolfaghari, Vahid
Knoll, Alois
contents We propose a novel model- and feature-based approach to development of vehicle software systems, where the end architecture is not explicitly defined. Instead, it emerges from an iterative process of search and optimization given certain constraints, requirements and hardware architecture, while retaining the property of single-system illusion, where applications run in a logically uniform environment. One of the key points of the presented approach is the inclusion of modern generative AI, specifically Large Language Models (LLMs), in the loop. With the recent advances in the field, we expect that the LLMs will be able to assist in processing of requirements, generation of formal system models, as well as generation of software deployment specification and test code. The resulting pipeline is automated to a large extent, with feedback being generated at each step.
format Preprint
id arxiv_https___arxiv_org_abs_2403_14460
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Towards Single-System Illusion in Software-Defined Vehicles -- Automated, AI-Powered Workflow
Lebioda, Krzysztof
Vorobev, Viktor
Petrovic, Nenad
Pan, Fengjunjie
Zolfaghari, Vahid
Knoll, Alois
Software Engineering
Artificial Intelligence
Computation and Language
D.2.1; D.2.2; D.2.4; I.2.7; I.2.2; I.7.0
We propose a novel model- and feature-based approach to development of vehicle software systems, where the end architecture is not explicitly defined. Instead, it emerges from an iterative process of search and optimization given certain constraints, requirements and hardware architecture, while retaining the property of single-system illusion, where applications run in a logically uniform environment. One of the key points of the presented approach is the inclusion of modern generative AI, specifically Large Language Models (LLMs), in the loop. With the recent advances in the field, we expect that the LLMs will be able to assist in processing of requirements, generation of formal system models, as well as generation of software deployment specification and test code. The resulting pipeline is automated to a large extent, with feedback being generated at each step.
title Towards Single-System Illusion in Software-Defined Vehicles -- Automated, AI-Powered Workflow
topic Software Engineering
Artificial Intelligence
Computation and Language
D.2.1; D.2.2; D.2.4; I.2.7; I.2.2; I.7.0
url https://arxiv.org/abs/2403.14460