Abstract
Conceptual models are often underused in agile contexts. Large Language Models (LLMs) open new avenues to automatically derive such models from agile requirements artifacts. This could potentially reduce documentation effort and reconnect agile practice with model-driven engineering. This study investigates whether LLMs can transform user stories and BDD scenarios into UML use case diagrams and BPMN workflows of sufficient quality for professional requirements engineering practice. Using GPT-o3, the research explores four factors affecting LLM-generated models: prompting strategy, output consistency, comparative model quality, and the impact of expert feedback. Evaluation employs the Lindland–Moody quality framework across syntactic, semantic, pragmatic, and completeness dimensions. As an exploratory feasibility study, results demonstrate promising automation potential while highlighting current limitations in precision, consistency, and pragmatic adequacy.
Paper Type
Short Paper
DOI
10.62036/ISD.2026.31
Towards LLM-Based Conceptual Modeling from User Stories and Behavior-Driven Development Scenarios in Agile Requirements Engineering
Conceptual models are often underused in agile contexts. Large Language Models (LLMs) open new avenues to automatically derive such models from agile requirements artifacts. This could potentially reduce documentation effort and reconnect agile practice with model-driven engineering. This study investigates whether LLMs can transform user stories and BDD scenarios into UML use case diagrams and BPMN workflows of sufficient quality for professional requirements engineering practice. Using GPT-o3, the research explores four factors affecting LLM-generated models: prompting strategy, output consistency, comparative model quality, and the impact of expert feedback. Evaluation employs the Lindland–Moody quality framework across syntactic, semantic, pragmatic, and completeness dimensions. As an exploratory feasibility study, results demonstrate promising automation potential while highlighting current limitations in precision, consistency, and pragmatic adequacy.
Recommended Citation
van Bon, J., Poelmans, S. & Wautelet, Y.(2026). Towards LLM-Based Conceptual Modeling from User Stories and Behavior-Driven Development Scenarios in Agile Requirements Engineering. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.31