How LLMs Aid in UML Modeling: An Exploratory Study with Novice Analysts

• URL: http://arxiv.org/abs/2404.17739v2
• Date: Mon, 10 Jun 2024 17:29:16 GMT
• Title: How LLMs Aid in UML Modeling: An Exploratory Study with Novice Analysts
• Authors: Beian Wang, Chong Wang, Peng Liang, Bing Li, Cheng Zeng,
• Abstract summary: GPT-3, Large Language Models (LLMs) have caught the eyes of researchers, practitioners, and educators in the field of software engineering. This paper explores how LLMs can assist novice analysts in creating three types of typical models: use case models, class diagrams, and sequence diagrams.
• Score: 9.517655899237413
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Since the emergence of GPT-3, Large Language Models (LLMs) have caught the eyes of researchers, practitioners, and educators in the field of software engineering. However, there has been relatively little investigation regarding the performance of LLMs in assisting with requirements analysis and UML modeling. This paper explores how LLMs can assist novice analysts in creating three types of typical UML models: use case models, class diagrams, and sequence diagrams. For this purpose, we designed the modeling tasks of these three UML models for 45 undergraduate students who participated in a requirements modeling course, with the help of LLMs. By analyzing their project reports, we found that LLMs can assist undergraduate students as novice analysts in UML modeling tasks, but LLMs also have shortcomings and limitations that should be considered when using them.

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