4 papers
Knowledge-Graph-Guided Retrieval-Augmented LLMs for Explainable Root Cause Analysis in Automotive HiL Validation
Hamza Ouarrad, Mohammad Abboush, Andreas Rausch
Hardware-in-the-Loop validation of automotive software systems generates large multivariate time-series recordings whose manual analysis is time-consuming and often limited to anom…
LLM Ensemble Fault Classification for Automotive HiL Validation
Hamza Ouarrad, Mohammad Abboush, Andreas Rausch
Automotive HiL validation generates large multivariate test recordings whose analysis remains challenging due to manual review effort, rule-based limitations, and the need for expl…
Sensor-Level Fault Diagnosis for Automotive Software Validation Using Large Language Models
Mohammad Abboush, Hamza Ouarrad, Andreas Rausch
The pre-series validation of automotive software on hardware-in-the-loop (HIL) platforms produces large volumes of multivariate sensor recordings whose assessment against functiona…
Fault Detection and Explainable Classification in Automotive HIL Validation via Denoising Autoencoders and In-Context Large Language Models
Mohammad Abboush, Hamza Ouarrad, Andreas Rausch
Validating automotive software systems produces large multivariate test recordings that are still examined through effort-intensive manual review and rule-based evaluation, which d…