A Systematic Review of Artificial Intelligence for Software Requirements in Open-Source Software

Abstract

Software stakeholders have seamlessly integrated artificial intelligence technologies into the requirements engineering processes for open-source software, which presents both opportunities and challenges. This systematic literature review examines the current state of artificial intelligence application in requirements engineering for open-source software and emphasizes the opportunities and challenges faced by practitioners. Based on the reviewed literature, artificial intelligence technologies, such as machine learning, natural language processing, large language models, and deep learning techniques, have been increasingly applied to support key requirements engineering activities, particularly requirements elicitation, classification, prioritization, and stakeholder analysis. However, the lack of structured data in open-source software directly challenges the effectiveness of artificial intelligence solutions for requirements engineering processes. The findings highlight the need for future research to focus on finding viable solutions to these identified issues. This review provides a consolidated overview for researchers and practitioners interested in enhancing artificial intelligence integration into requirements engineering for open-source software projects and provides guidance for future research to effectively address existing challenges and facilitate integration of AI techniques.