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Published April 3, 2026 | Version v1
Dataset Open

AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub

  • 1. ROR icon University of Nevada, Las Vegas
  • 2. ROR icon Mbarara University of Science and Technology

Description

Software Engineering 3.0 marks a paradigm shift in software development in which AI coding agents are no longer just assistive tools but active contributors. While prior empirical studies have examined productivity gains and acceptance patterns in AI-assisted development, the challenges associated with integrating agent-generated contributions remain less understood. In particular, merge conflicts, a fundamental aspect of collaborative software development, have received limited attention in this emerging context. In this paper, we present AgenticFlict, a large-scale dataset of textual merge conflicts in AI coding agent pull requests (Agentic PRs). The dataset comprises 142K+ Agentic PRs collected from 59K+ repositories, of which 107K+ are successfully processed through deterministic merge simulation. Our pipeline identifies 29K+ PRs exhibiting merge conflicts, yielding a conflict rate of 27.67%, and extracts 336K+ fine-grained conflict regions across these instances. Our preliminary exploratory analysis indicates that merge conflicts are both frequent and often substantial in AI-generated contributions, with noticeable variation across agents, emphasizing the need to better understand and manage integration challenges in AI-assisted software development.

Notes

If you use AgenticFlict in your research, please cite both the dataset and the companion paper:
 
@dataset{agenticflict2026,
title = {AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub},
author = {Ogenrwot, Daniel and Businge, John},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.19396916},
url = {https://doi.org/10.5281/zenodo.19396916}
}
 
@article{agenticflict2026paper,
title = {AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub},
author = {Ogenrwot, Daniel and Businge, John},
year = {2026},
journal = {arXiv preprint arXiv:2604.03551},
url = {https://arxiv.org/abs/2604.03551}
}

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Related works

Is supplement to
Publication: arXiv:2604.03551 (arXiv)

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