Automating Software Documentation: Employing LLMs for Precise Use Case Description
Lahbib Naimi, El Mahi Bouziane, Abdeslam Jakimi, Rachid Saadane, Abdellah Chehri
Abstract
The creation of software documentation is widely recognized as a critical and demanding undertaking within the rapidly changing realm of software development. This study introduces a novel method for generating software documentation by leveraging Large Language Models (LLM). The paper presents a novel system that extracts use cases from UML Use Case Diagrams and employs a Generative AI Model to generate descriptive text for each extracted use case. This approach aims to reduce the amount of time dedicated to documentation and encourage uniformity in the description of software functions. The results suggest that the level of manual labor and time needed can be substantially decreased by upholding elevated levels of clarity and comprehensiveness in software documentation. This study presents a use-case scenario that showcases the practical application of our methodology in real-world situations. The purpose of this example is to demonstrate the practicality and effectiveness of the method.