2025/12/22 by Yuwon Yoon, Yoon, Yuwon, Kevin Iwan +9
Computer Science · Decision Sciences · #Construction Project Management and Performance #FOS: Computer and information sciences #Resource-Constrained Project Scheduling #Software Engineering (cs.SE) #Software Engineering Techniques and Practices
paper · doi:10.48550/arxiv.2512.18966
openalex publication_date 2025/12/22 · openalex created_date 2025/12/24 · openalex updated_date 2026/07/28
Planning for an upcoming project iteration (sprint) is one of the key activities in Scrum planning. In this paper, we present our work in progress on exploring the applicability of Large Language Models (LLMs) for solving this problem. We conducted case studies with manually created data sets to investigate the applicability of OpenAI models for supporting the sprint planning activities. In our experiments, we applied three models provided OpenAI: GPT-3.5 Turbo, GPT-4.0 Turbo, and Val. The experiments demonstrated that the results produced by the models aren't of acceptable quality for direct use in Scrum projects.