---
title: DeNovoSWE
canonical_url: "https://www.modelscope.cn/datasets/AweAI-Team/DeNovoSWE"
md_url: "https://www.modelscope.cn/datasets/AweAI-Team/DeNovoSWE.md"
repository: AweAI-Team/DeNovoSWE
last_updated: 2026-06-14
license: cc-by-4.0
downloads: 2307
stars: 0
---

# DeNovoSWE

> DeNovoSWE - AweAI-Team 在 ModelScope 开源的数据集。DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch

AweAI-Team/DeNovoSWE 是 ModelScope 魔搭社区上的数据集，采用 cc-by-4.0 许可。

- **Repository**: AweAI-Team/DeNovoSWE
- **License**: cc-by-4.0
- **Downloads**: 2307
- **Stars**: 0
- **Last updated**: 2026-06-14

Source: https://www.modelscope.cn/datasets/AweAI-Team/DeNovoSWE

---

# DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch

<div align="center">

[![arXiv](https://img.shields.io/badge/arXiv-2606.10728-b31b1b.svg)](https://huggingface.co/papers/2606.10728)
[![Hugging Face Datasets](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Datasets-blue)](https://huggingface.co/collections/AweAI-Team/denovoswe)
[![GitHub](https://img.shields.io/badge/GitHub-Repository-181717?logo=github&logoColor=white)](https://github.com/AweAI-Team/DeNovoSWE)
[![License](https://img.shields.io/badge/License-CC%20BY%204.0-green.svg)](LICENSE)
<br>

</div>

DeNovoSWE is a large-scale dataset for whole-repository generation, as introduced in the paper "[DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch](https://huggingface.co/papers/2606.10728)".

![](figures/main.png)

## 🔥 Highlights
- 4,818 high-quality instances.
- 11k filtered trajectories from 34k DeepSeek-v4-High trajectories.
- Strong performance: 50% in BeyondSWE-Doc2Repo trained from Qwen3.5-35B-A3B.

## 📣 News
- **2026-06-10** 🚀 We released part of our data on [Hugging Face](https://huggingface.co/collections/AweAI-Team/denovoswe). from DeepSeek-v4-High. 
- **2026-06-10** 📝 Our paper [**"DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch"**](https://huggingface.co/papers/2606.10728) is now available on arXiv.


## FAQ
- For evaluation of DeNovoSWE-Data, you can use AweAgent and refer to this [recipe](https://github.com/AweAI-Team/AweAgent/tree/main/recipes/denovo_swe).

## 📊 Data Format
| Field | Description |
|---|---|
| `instance_id` | Unique identifier for each benchmark instance. |
| `document` | Ground-truth documentation provided to the agent for repository reconstruction. |
| `pypi_name` | PyPI package name used to enforce anti-cheating constraints during evaluation. |
| `image_url` | URL of the Docker image configured for the environment. |
| `user` | GitHub username or organization owning the repository. |
| `repo` | Name of the target GitHub repository. |
| `workdir` | Working directory path of the repository inside the Docker container. |
| `unit_test` | List of all unit test identifiers. |
| `test_patch` | Code patch for unit tests, applied during the evaluation phase. |
| `test_binary_files` | Binary files used by unit tests that are unsuitable for standard text patching. |

## 🤖 Results

![](figures/performance.png)

## DeNovoSWE-Agent
Key parameters can be seen below:

| Parameter | Value |
| :--- | :--- |
| Max turns | 500 |
| Max sequence length | 256k |
| Temperature | 1 |


## 📖 Citation

If you find this project useful for your research, please consider citing our paper:
```bibtex
@misc{zhao2026denovoswescalinglonghorizonenvironments,
      title={DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch}, 
      author={Jiale Zhao and Guoxin Chen and Fanzhe Meng and Wayne Xin Zhao and Ruihua Song and Ji-Rong Wen and Kai Jia},
      year={2026},
      eprint={2606.10728},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2606.10728}, 
}
```

## 📄 License

This project is licensed under the CC BY 4.0 License - see the [LICENSE](LICENSE) file for details.

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<div align="center">

**If you find this project useful, please consider giving it a ⭐ !**

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