Core Concepts
Proposing a novel model- and feature-based approach to software development for vehicles, integrating generative AI to automate the process and achieve a single-system illusion.
Abstract
The content introduces a new approach to developing software systems for vehicles, emphasizing the emergence of architecture from iterative processes. It highlights the role of generative AI, specifically Large Language Models (LLMs), in automating various stages of software development. The proposed workflow aims to provide a single-system illusion where applications run in a logically uniform environment. The document is structured into sections discussing the introduction, methodology, scope, complementary work, limitations, conclusion, and glossary. Key insights include challenges in traditional software development paradigms, the impact of rising system complexity on costs, the shift towards software-defined vehicles in the automotive industry, and the importance of model-based system engineering coupled with design by contract principles.
Introduction:
Rising costs in vehicle software development.
Limitations of classical software development paradigms.
Model-Based System Engineering:
Importance of MBSE and design by contract principles.
Role of Generative AI:
Leveraging LLMs for automating requirements processing and code generation.
Resource Allocation:
Mapping software components to hardware based on optimization criteria.
Code Generation and Deployment:
Using generative AI for creating working code adapted to specific architectures.
Scope and Limitations:
Areas for future research including handling conflicting requirements and improving hardware representation automatically.
Conclusion:
Advocating for an extended software development process using generative AI.
Stats
The costs of vehicle software development are estimated to double by 2030 compared to 2020.
Software-defined vehicles are becoming popular due to changes mainly driven by software updates.
Model-Based Systems Engineering (MBSE) is crucial for enabling software-defined vehicles.
Large Language Models (LLMs) are used in automating various stages of software development.
Generative AI assists in defining a new paradigm beyond current standards.
Quotes
"Classical software development paradigms are very rigid and slow to adapt." - [Kumar & Bhatia]
"Software-defined vehicles are becoming the new trend in the automotive industry." - [Islam et al.]
"The advantage of using AI over classical tools is the generative power of models." - [Pan et al.]