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license: mit
pretty_name: SWE-Next Repository List with NEW_COMMIT_BETTER Counts
language:
- en
size_categories:
- 100<n<1K
configs:
- config_name: default
data_files:
- split: train
path: new_commit_better_repos.csv
---
<div align="center">
<h1>SWE-Next: Scalable Real-World Software Engineering Tasks for Agents</h1>
</div>
<div align="center">
<a href="https://arxiv.org/abs/2603.20691"><img alt="Paper" src="https://img.shields.io/badge/Paper-arXiv-b31b1b?style=for-the-badge&logo=arxiv&logoColor=white"></a>
<a href="https://tiger-ai-lab.github.io/SWE-Next/"><img alt="Project Page" src="https://img.shields.io/badge/Project%20Page-Website-4285F4?style=for-the-badge&logo=googlechrome&logoColor=white"></a>
<a href="https://github.com/TIGER-AI-Lab/SWE-Next"><img alt="Code" src="https://img.shields.io/badge/Code-GitHub-181717?style=for-the-badge&logo=github&logoColor=white"></a>
<a href="https://huggingface.co/datasets/TIGER-Lab/SWE-Next"><img alt="Dataset" src="https://img.shields.io/badge/Base%20Dataset-HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000"></a>
<a href="https://huggingface.co/datasets/TIGER-Lab/SWE-Next-SFT-Trajectories"><img alt="SFT Trajs" src="https://img.shields.io/badge/SFT%20Trajs-HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000"></a>
<a href="https://huggingface.co/TIGER-Lab/SWE-Next-7B"><img alt="Model 7B" src="https://img.shields.io/badge/Model%207B-HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000"></a>
<a href="https://huggingface.co/TIGER-Lab/SWE-Next-14B"><img alt="Model 14B" src="https://img.shields.io/badge/Model%2014B-HuggingFace-FFD21E?style=for-the-badge&logo=huggingface&logoColor=000"></a>
</div>
# new_commit_better_repos
This repository contains `new_commit_better_repos.csv`, an intermediate SWE-Next metadata artifact listing repositories with at least one observed `NEW_COMMIT_BETTER` commit pair during collection. Each row records a GitHub repository and the number of commit pairs in that repository that produced strict test improvements without regressions.
The file contains **335** repositories and is used by the SWE-Next pipeline as a lightweight index of promising repositories before final task packaging.
## Overview
SWE-Next starts from **3,971** seeded Python repositories and executes **102,582** candidate base/merged commit pairs mined from real merged PRs. During this process, repositories that exhibit at least one `NEW_COMMIT_BETTER` outcome are tracked in this CSV. The file therefore serves as an upstream repository-level summary rather than the final released task dataset.
## Format
The CSV has two columns:
| Column | Description |
|---|---|
| `repo` | GitHub repository in `owner/repo` format |
| `NEW_COMMIT_BETTER` | Number of commit pairs in that repository classified as `NEW_COMMIT_BETTER` |
Example rows:
```csv
repo,NEW_COMMIT_BETTER
pydantic/pydantic,152
yt-dlp/yt-dlp,62
pytest-dev/pyfakefs,56
```
## Files
- `new_commit_better_repos.csv`: repository-level summary of observed `NEW_COMMIT_BETTER` counts
## Usage
This artifact is mainly useful for:
- inspecting which repositories contribute execution-grounded improvements,
- selecting promising repositories for further pipeline runs,
- reproducing intermediate repository-level filtering stages in SWE-Next.
Load it with pandas:
```python
import pandas as pd
df = pd.read_csv("hf://datasets/TIGER-Lab/new_commit_better_repos/new_commit_better_repos.csv")
print(df.head())
```
## Relationship to the SWE-Next Release
This repo contains a repository-level intermediate artifact used by SWE-Next. Related artifacts are available separately:
- **Seed repository list**: `TIGER-Lab/packages_python_filtered`
- **Final task dataset**: `TIGER-Lab/SWE-Next`
- **SFT trajectories**: `TIGER-Lab/SWE-Next-SFT-Trajectories`
- **Project code**: `github.com/TIGER-AI-Lab/SWE-Next`
## Citation
```bibtex
@misc{liang2026swenextscalablerealworldsoftware,
title={SWE-Next: Scalable Real-World Software Engineering Tasks for Agents},
author={Jiarong Liang and Zhiheng Lyu and Zijie Liu and Xiangchao Chen and Ping Nie and Kai Zou and Wenhu Chen},
year={2026},
eprint={2603.20691},
archivePrefix={arXiv},
primaryClass={cs.SE},
url={https://arxiv.org/abs/2603.20691},
}
```
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