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Volume 14
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10.3390/systems14030302
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Article

Identification of Physical Boundary Conditions for Mechatronic Test-Case Generation Using Large Language Models and MBSE System Models

by
Matthias May
*,
Georg Jacobs
,
Simon Dehn
,
Gregor Höpfner
,
Thilo Zerwas
,
Kathrin Boelsen
and
Sebastian Hacker
Institute for Machine Elements and Systems Engineering IMSE, RWTH Aachen University, 52056 Aachen, Germany
*
Author to whom correspondence should be addressed.
Systems 2026, 14(3), 302; https://doi.org/10.3390/systems14030302
Submission received: 9 January 2026 / Revised: 3 March 2026 / Accepted: 10 March 2026 / Published: 12 March 2026
(This article belongs to the Special Issue Digital and Data-Driven Systems Engineering: Bridging Theory and Practice)
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Abstract

Future cyber-physical systems (CPSs), integrating subsystems of the mechanical, electrical and software domains, are becoming increasingly interconnected and complex. As complexity grows, testing effort increases as well. This includes the test-case definition step, where the test targets and boundary conditions are specified. With rising system complexity, the effort required to ensure that all relevant conditions for each test target are identified increases. Manual test-case definition remains the norm, creating effort bottlenecks in ensuring systematic coverage and compliance with standards such as ISO 26262 and ISO 29119. This paper explores how large language models (LLMs) can support the identification of complex boundary conditions for CPS test cases through detailed requirement analysis. The impact of performing taxonomy-guided, structured requirement mapping prior to test-case generation was evaluated by comparing it with a version without this guidance. Furthermore, the influence of supplying a Model-Based Systems Engineering (MBSE) system model as context information via Graph RAG is examined. The results show that structured, stepwise reasoning significantly improves reliability and consistency over unguided generation, while system-model information provides valuable contextual insight but has a minor impact in the chosen example. These findings outline a scalable framework for AI-assisted test-case generation.
Keywords: Large Language Models (LLMs); Model-Based Systems Engineering (MBSE); automated test case derivation Large Language Models (LLMs); Model-Based Systems Engineering (MBSE); automated test case derivation
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MDPI and ACS Style

May, M.; Jacobs, G.; Dehn, S.; Höpfner, G.; Zerwas, T.; Boelsen, K.; Hacker, S. Identification of Physical Boundary Conditions for Mechatronic Test-Case Generation Using Large Language Models and MBSE System Models. Systems 2026, 14, 302. https://doi.org/10.3390/systems14030302

AMA Style

May M, Jacobs G, Dehn S, Höpfner G, Zerwas T, Boelsen K, Hacker S. Identification of Physical Boundary Conditions for Mechatronic Test-Case Generation Using Large Language Models and MBSE System Models. Systems. 2026; 14(3):302. https://doi.org/10.3390/systems14030302

Chicago/Turabian Style

May, Matthias, Georg Jacobs, Simon Dehn, Gregor Höpfner, Thilo Zerwas, Kathrin Boelsen, and Sebastian Hacker. 2026. "Identification of Physical Boundary Conditions for Mechatronic Test-Case Generation Using Large Language Models and MBSE System Models" Systems 14, no. 3: 302. https://doi.org/10.3390/systems14030302

APA Style

May, M., Jacobs, G., Dehn, S., Höpfner, G., Zerwas, T., Boelsen, K., & Hacker, S. (2026). Identification of Physical Boundary Conditions for Mechatronic Test-Case Generation Using Large Language Models and MBSE System Models. Systems, 14(3), 302. https://doi.org/10.3390/systems14030302

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