307 citations
- Auckland University of TechnologyNZ5 papers
- Leibniz University HannoverDE5 papers
- IT University of CopenhagenDK4 papers
- Karlsruhe Institute of TechnologyDE4 papers
- Reutlingen UniversityDE4 papers
- Technical University of MunichDE4 papers
- TU WienAT4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- The University of Texas at AustinUS3 papers
- University of TartuEE3 papers
- Aix-Marseille UniversitéFR2 papers
- Board of the Swiss Federal Institutes of TechnologyCH2 papers
23 papers · 1 filter
Representative Dataset Generation Framework for AI-based Failure Analysis during real-time Validation of Automotive Software Systems
Mohammad Abboush, Christoph Knieke, Andreas Rausch
Recently, thanks to its ability to extract knowledge from historical datasets, the data-driven approach has been widely used in various phases of the system development life cycle.…
Describing Agentic AI Systems with C4: Lessons from Industry Projects
Andreas Rausch, Stefan Wittek
Different domains foster different architectural styles -- and thus different documentation practices (e.g., state-based models for behavioral control vs. ER-style models for infor…
An explainable hybrid deep learning-enabled intelligent fault detection and diagnosis approach for automotive software systems validation
Mohammad Abboush, Ehab Ghannoum, Andreas Rausch
Advancements in data-driven machine learning have emerged as a pivotal element in supporting automotive software systems (ASSs) engineering across various levels of the V-developme…
Modeling and Recovering Hierarchical Structural Architectures of ROS 2 Systems from Code and Launch Configurations using LLM-based Agents
Mohamed Benchat, Dominique Briechle, Raj Chanchad +9
Model-Driven Engineering (MDE) relies on explicit architecture models to document and evolve systems across abstraction levels. For ROS~2, subsystem structure is often encoded impl…
Towards Benchmarking Design Pattern Detection Under Obfuscation: Reproducing and Evaluating Attention-Based Detection Method
Manthan Shenoy, Andreas Rausch
This paper investigates the semantic robustness of attention-based classifiers for design pattern detection, particularly focusing on their reliance on structural and behavioral se…
LLMs-Powered Real-Time Fault Injection: An Approach Toward Intelligent Fault Test Cases Generation
Mohammad Abboush, Ahmad Hatahet, Andreas Rausch
A well-known testing method for the safety evaluation and real-time validation of automotive software systems (ASSs) is Fault Injection (FI). In accordance with the ISO 26262 stand…