ICSE 2024
Fri 12 - Sun 21 April 2024 Lisbon, Portugal

Digital twins are used to simulate (cyber-physical) systems and offer great benefits for testing and verification. The importance of quickly and efficiently constructing digital twins increases with the appearance of devices of greater complexity. Furthermore, the more (varied) behaviour the digital twin captures of the simulated device the more use cases it can be used for. In the presented thesis we investigate methods from automata learning and machine learning to automatically synthesise digital twins from cyber-physical systems, capturing both discrete and continuous behaviour. Our aim hereby is to combine methods from both fields and utilize their respective strengths to build better digital twins from cyber-physical systems in practice. We already developed an algorithm that learns discrete behavioural models even in the presence of noisy data.

Tue 16 Apr

Displayed time zone: Lisbon change

14:00 - 15:30
Focus Group: Software Models and SimulationsDoctoral Symposium at Fernando Pessoa
Chair(s): Matthew B Dwyer University of Virginia
14:00
90m
Poster
Automated Model Quality Estimation and Change Impact Analysis on Model Histories
Doctoral Symposium
14:00
90m
Poster
Sustainable Software Engineering: Visions and Perspectives beyond Energy Efficiency
Doctoral Symposium
Christoph König Karlsruhe Institute of Technology
14:00
90m
Poster
Learning Models of Cyber-Physical Systems with Discrete and Continuous Behaviour for Digital Twin Synthesis
Doctoral Symposium
Felix Wallner Graz University of Technology, Institute of Software Technology
File Attached
14:00
90m
Poster
Resolving Goal-Conflicts and Scaling Synthesis through Mode-Based Decomposition
Doctoral Symposium
Matías Brizzio IMDEA Software Institute
Link to publication DOI
14:00
90m
Poster
Simulation-based Testing of Automated Driving Systems
Doctoral Symposium
Fauzia Khan University of Tartu, Estonia