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20242026
most citedMulti-modal Summarization in Model-Based Engineering: Automotive Software Development Case Study

1 citations · 1 across the 18 of their papers we have counts for

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14 papers · 1 filter

cs.SE2026

LLM-Empowered Functional Safety and Security by Design in Automotive Systems

Nenad Petrovic, Vahid Zolfaghari, Fengjunjie Pan +1

This paper presents LLM-empowered workflow to support Software Defined Vehicle (SDV) software development, covering the aspects of security-aware system topology design, as well as…

cs.SE2025

LLM-Empowered Event-Chain Driven Code Generation for ADAS in SDV systems

Nenad Petrovic, Norbert Kroth, Axel Torschmied +9

This paper presents an event-chain-driven, LLM-empowered workflow for generating validated, automotive code from natural-language requirements. A Retrieval-Augmented Generation (RA…

cs.SE2025

Hallucination in LLM-Based Code Generation: An Automotive Case Study

Marc Pavel, Nenad Petrovic, Lukasz Mazur +3

Large Language Models (LLMs) have shown significant potential in automating code generation tasks offering new opportunities across software engineering domains. However, their pra…

cs.SE2025

GenAI for Automotive Software Development: From Requirements to Wheels

Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari +3

This paper introduces a GenAI-empowered approach to automated development of automotive software, with emphasis on autonomous and Advanced Driver Assistance Systems (ADAS) capabili…

cs.SE2025

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code

Nenad Petrovic, Vahid Zolfaghari, Andre Schamschurko +10

Adoption of state-of-art Generative Artificial Intelligence (GenAI) aims to revolutionize many industrial areas by reducing the amount of human intervention needed and effort for h…

cs.SE2025

Are requirements really all you need? A case study of LLM-driven configuration code generation for automotive simulations

Krzysztof Lebioda, Nenad Petrovic, Fengjunjie Pan +3

Large Language Models (LLMs) are taking many industries by storm. They possess impressive reasoning capabilities and are capable of handling complex problems, as shown by their ste…

cs.SE2025

Automating Automotive Software Development: A Synergy of Generative AI and Model-Based Methods

Fengjunjie Pan, Yinglei Song, Long Wen +3

As the automotive industry shifts its focus toward software-defined vehicles, the need for faster and reliable software development continues to grow. However, traditional methods…

cs.SE2025

LLM-enabled Instance Model Generation

Fengjunjie Pan, Nenad Petrovic, Vahid Zolfaghari +2

In the domain of model-based engineering, models are essential components that enable system design and analysis. Traditionally, the creation of these models has been a manual proc…

cs.SE2025

LLM-based Iterative Approach to Metamodeling in Automotive

Nenad Petrovic, Fengjunjie Pan, Vahid Zolfaghari +1

In this paper, we introduce an automated approach to domain-specific metamodel construction relying on Large Language Model (LLM). The main focus is adoption in automotive domain.…

cs.SE2025★ 1 cited

Multi-modal Summarization in Model-Based Engineering: Automotive Software Development Case Study

Nenad Petrovic, Yurui Zhang, Moaad Maaroufi +5

Multimodal summarization integrating information from diverse data modalities presents a promising solution to aid the understanding of information within various processes. Howeve…

cs.SE2024

Adopting RAG for LLM-Aided Future Vehicle Design

Vahid Zolfaghari, Nenad Petrovic, Fengjunjie Pan +2

In this paper, we explore the integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) to enhance automated design and software development in the auto…

cs.SE2024

Automatic Platform Configuration and Software Integration for Software-Defined Vehicles

Fengjunjie Pan, Jianjie Lin, Markus Rickert

In the automotive industry, platform configuration and software integration are mostly manual tasks performed during the development phase, requiring consideration of various safet…

cs.SE2024

Synergy of Large Language Model and Model Driven Engineering for Automated Development of Centralized Vehicular Systems

Nenad Petrovic, Fengjunjie Pan, Krzysztof Lebioda +6

We present a prototype of a tool leveraging the synergy of model driven engineering (MDE) and Large Language Models (LLM) for the purpose of software development process automation…

cs.SE2024

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

Krzysztof Lebioda, Viktor Vorobev, Nenad Petrovic +3

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 i…