English

Scrum Sprint Planning: LLM-based and algorithmic solutions

Software Engineering 2025-12-23 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2512.18966,
  title  = {Scrum Sprint Planning: LLM-based and algorithmic solutions},
  author = {Yuwon Yoon and Kevin Iwan and Madeleine Zwart and Xiaohan Qin and Hina Lee and Maria Spichkova},
  journal= {arXiv preprint arXiv:2512.18966},
  year   = {2025}
}
R2 v1 2026-07-01T08:36:01.590Z