Related papers: GenAI-Enabled Backlog Grooming in Agile Software Projects: An Empirical Study

GenAI-Enabled Backlog Grooming in Agile Software Projects: An Empirical Study

URL: http://arxiv.org/abs/2507.10753v1
Date: Mon, 14 Jul 2025 19:22:57 GMT
Title: GenAI-Enabled Backlog Grooming in Agile Software Projects: An Empirical Study
Authors: Kasper Lien Oftebro, Anh Nguyen-Duc, Kai-Kristian Kemell,
Abstract summary: This study investigates whether a generative-AI (GenAI) assistant can automate backlog grooming in Agile software projects without sacrificing accuracy or transparency.<n>We developed a Jira plug-in that embeds backlog issues with the vector database, detects duplicates via cosine similarity, and leverage the GPT-4o model to propose merges, deletions, or new issues.
Score: 2.9073118555228232
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Effective backlog management is critical for ensuring that development teams remain aligned with evolving requirements and stakeholder expectations. However, as product backlogs consistently grow in scale and complexity, they tend to become cluttered with redundant, outdated, or poorly defined tasks, complicating prioritization and decision making processes. This study investigates whether a generative-AI (GenAI) assistant can automate backlog grooming in Agile software projects without sacrificing accuracy or transparency. Through Design Science cycles, we developed a Jira plug-in that embeds backlog issues with the vector database, detects duplicates via cosine similarity, and leverage the GPT-4o model to propose merges, deletions, or new issues. We found that AI-assisted backlog grooming achieved 100 percent precision while reducing the time-to-completion by 45 percent. The findings demonstrated the tool's potential to streamline backlog refinement processes while improving user experiences.

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