Authors :
Martina Basic; Marko Vujasinovic
Volume/Issue :
Volume 11 - 2026, Issue 1 - January
Google Scholar :
https://tinyurl.com/y4r34dxs
Scribd :
https://tinyurl.com/mumtcakw
DOI :
https://doi.org/10.38124/ijisrt/26jan1576
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
LLMs have become increasingly popular tools for assisting software engineering tasks and specifically with automating the creation of UML design artefacts from requirements specified in a natural language. This work reports on the effectiveness of using LLM technologies to perform the translation of UML use-case diagrams into UML class Diagrams. Such task is traditionally performed by a human and requires both domain understanding and modeling expertise, however, it can be a tedious and labor-intensive manual task prone to errors during its process. Automated creation of UML class Diagrams from UML use-case diagrams requires LLMs to identify the domain entities, the responsibilities of each of those domain entities, and how domain entities relate to each other and therefore creating unique classes. The evaluation part of the work uses several use-case diagrams of varying levels of complexity to complete this task. The results showed that LLMs can effectively identify the crucial domain entities and provide class structures, and to alleviate the modelling efforts. However, there are still issues with the interpretation of ambiguous requirements and the maintenance of their associated semantics. Overall, LLM technologies are an effective aid to the early-stage development of UML class Diagrams; however, the final quality of the UML models is very dependent upon the domain experts that provide further guidance to the LLMs.
Keywords :
LLM; UML Class Diagram; UML Use-Case Diagram, Requirements Specification.
References :
- Object Management Group, 2017. Unified Modeling Language (UML), version 2.5.1. https://www.omg.org/spec/UML/2.5.1/About-UML
- Rouabhia, D., & Hadjadj, I., 2024. Enhancing class diagram dynamics: A natural language approach with ChatGPT. arXiv. https://arxiv.org/abs/2406.11002
- Zhao, L., Alhoshan, W., Ferrari, A., Letsholo, K.J., Ajagbe, M.A., Chioasca, E.V. and Batista-Navarro, R.T., 2021. Natural language processing for requirements engineering: A systematic mapping study. ACM Computing Surveys (CSUR), 54(3), pp.1-41.
- Cámara, J., Troya, J., Burgueño, L. and Vallecillo, A., 2023. On the assessment of generative AI in modeling tasks: an experience report with ChatGPT and UML. Software and Systems Modeling, 22(3), pp.781-793.
- Al-Ahmad, B., Alsobeh, A., Meqdadi, O. and Shaikh, N., 2025. A Student-Centric Evaluation Survey to Explore the Impact of LLMs on UML Modeling. Information, 16(7), p.565.
- De Bari, D., Garaccione, G., Coppola, R., Torchiano, M. and Ardito, L., 2024, October. Evaluating large language models in exercises of uml class diagram modeling. In Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (pp. 393-399).
- Giannouris, P. and Ananiadou, S., 2025. NOMAD: A Multi-Agent LLM System for UML Class Diagram Generation from Natural Language Requirements. arXiv preprint arXiv:2511.22409.
- Babaalla, Z., Jakimi, A. and Oualla, M., 2025. LLM-Driven MDA Pipeline for Generating UML Class Diagrams and Code. IEEE Access.
- Ferrari, A., Abualhaija, S. and Arora, C., 2024, June. Model generation with LLMs: From requirements to UML sequence diagrams. In 2024 IEEE 32nd International Requirements Engineering Conference Workshops (REW) (pp. 291-300). IEEE.
LLMs have become increasingly popular tools for assisting software engineering tasks and specifically with automating the creation of UML design artefacts from requirements specified in a natural language. This work reports on the effectiveness of using LLM technologies to perform the translation of UML use-case diagrams into UML class Diagrams. Such task is traditionally performed by a human and requires both domain understanding and modeling expertise, however, it can be a tedious and labor-intensive manual task prone to errors during its process. Automated creation of UML class Diagrams from UML use-case diagrams requires LLMs to identify the domain entities, the responsibilities of each of those domain entities, and how domain entities relate to each other and therefore creating unique classes. The evaluation part of the work uses several use-case diagrams of varying levels of complexity to complete this task. The results showed that LLMs can effectively identify the crucial domain entities and provide class structures, and to alleviate the modelling efforts. However, there are still issues with the interpretation of ambiguous requirements and the maintenance of their associated semantics. Overall, LLM technologies are an effective aid to the early-stage development of UML class Diagrams; however, the final quality of the UML models is very dependent upon the domain experts that provide further guidance to the LLMs.
Keywords :
LLM; UML Class Diagram; UML Use-Case Diagram, Requirements Specification.