Development of an automatic class diagram generator using an AI-based GRU classification model and 5W1H heuristic rules

ABSTRACT In software development, software requirements and class diagrams are core components that are closely related to each other. Software requirements specify the system's functionality in natural language, while class diagrams are created using CASE tools to visually represent the system's structure and behavior based on these requirements. Although software requirements and class diagrams are complementary, ensuring consistency between them is challenging due to the ambiguity and vagueness inherent in natural language. To address this issue, research on automatically transforming natural language into class diagrams is actively being conducted; however, most of these studies focus on requirements written in English. In addition, existing research primarily emphasizes the grammatical structure of natural language requirements, which limits their ability to reflect the conceptual structures of specific domains. To overcome these limitations, this paper proposes a method for developing an automatic class diagram generator that utilizes AI-based GRU classification model and 5W1H-based heuristic rules. The proposed class diagram generator extracts element and class model information from software requirements written in Korean and visualizes class diagrams based on a model interface language. For elements that can be directly extracted from natural language requirements, 5W1H-based heuristic rules considering linguistic characteristics are applied, while domain-specific elements requiring domain knowledge are extracted using an AI-based GRU classification model. Furthermore, when comparing the class diagrams generated by the proposed tool with those manually created by developers, the tool demonstrated high performance in terms of precision, recall, and F1-score.