20 citations · 64 across the 26 of their papers we have counts for
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Assessing Quantum Extreme Learning Machines for Software Testing in Practice
Asmar Muqeet, Hassan Sartaj, Aitor Arrieta +6
Machine learning has been extensively applied for classical software testing activities such as test generation, minimization, and prioritization. Along the same lines, there has b…
Foundation Models for the Digital Twin Creation of Cyber-Physical Systems
Shaukat Ali, Paolo Arcaini, Aitor Arrieta
Foundation models are trained on a large amount of data to learn generic patterns. Consequently, these models can be used and fine-tuned for various purposes. Naturally, studying s…
Search-based Automated Program Repair of CPS Controllers Modeled in Simulink-Stateflow
Aitor Arrieta, Pablo Valle, Shaukat Ali
Stateflow models are widely used in the industry to model the high-level control logic of Cyber-Physical Systems (CPSs) in Simulink--the defacto CPS simulator. Many approaches exis…
Reality Bites: Assessing the Realism of Driving Scenarios with Large Language Models
Jiahui Wu, Chengjie Lu, Aitor Arrieta +2
Large Language Models (LLMs) are demonstrating outstanding potential for tasks such as text generation, summarization, and classification. Given that such models are trained on a h…
Application of Quantum Extreme Learning Machines for QoS Prediction of Elevators' Software in an Industrial Context
Xinyi Wang, Shaukat Ali, Aitor Arrieta +2
Quantum Extreme Learning Machine (QELM) is an emerging technique that utilizes quantum dynamics and an easy-training strategy to solve problems such as classification and regressio…