  Integrating artificial intelligence (AI) into software engineering can
transform traditional practices by enhancing efficiency, accuracy, and
innovation. This study explores using ChatGPT, an advanced AI language model,
to enhance UML class diagrams dynamically, an underexplored area.
Traditionally, creating and maintaining class diagrams are manual,
time-consuming, and error-prone processes. This research leverages natural
language processing (NLP) techniques to automate the extraction of methods and
interactions from detailed use case tables and integrate them into class
diagrams.
  The methodology involves several steps: (1) developing detailed natural
language use case tables by master's degree students for a "Waste Recycling
Platform," (2) creating an initial static class diagram based on these tables,
(3) iteratively enriching the class diagram through ChatGPT integration to
analyze use cases and suggest methods, (4) reviewing and incorporating these
methods into the class diagram, and (5) dynamically updating the PlantUML
\cite{plantuml} class diagram, followed by evaluation and refinement. Findings
indicate that the AI-driven approach significantly improves the accuracy and
completeness of the class diagram. Additionally, dynamic enhancement aligns
well with Agile development practices, facilitating rapid iterations and
continuous improvement.
  Key contributions include demonstrating the feasibility and benefits of
integrating AI into software modeling tasks, providing a comprehensive
representation of system behaviors and interactions, and highlighting AI's
potential to streamline and improve existing software engineering processes.
Future research should address identified limitations and explore AI
applications in other software models.
