| title | DeNovoSWE: Scaling Long-Horizon Environments for Generating Entire Repositories from Scratch |
|---|---|
| authors | Jiale Zhao, Guoxin Chen, Fanzhe Meng, Wayne Xin Zhao, Ruihua Song, Ji-Rong Wen, Kai Jia |
| date | 2026-06-09 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2606.10728 |
| affiliation | AweAI Team |
| upvotes | 37 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| abstract | As the capabilities of LLM-based code agents continue to advance, their expected role is expanding beyond localized bug fixing in existing codebases toward architecting and implementing complete software repositories from high-level specifications. However, training agents for such long-horizon software engineering tasks remains difficult due to the scarcity of large-scale, verifiable whole-repository generation data. In this paper, we introduce DeNovoSWE, a large-scale dataset for whole-repository generation. DeNovoSWE comprises 4,818 high-quality instances, where each instance requires generating a complete repository from documentation. Our dataset is automatically constructed through a carefully designed sandboxed agentic workflow, enabling scalable curation without human annotation. DeNovoSWE is constructed with "divide and conquer" and critic-repair philosophy. To balance data quality and diversity, we further introduce a difficulty-aware trajectory filtering strategy. Fine-tuning Qwen3-30B-A3B on DeNovoSWE substantially improves long-horizon SWE performance, raising its score on the challenging BeyondSWE-Doc2Repo benchmark from 5.8% to 47.2%. |
cite
@misc{zhao2026denovoswe,
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},
url={https://arxiv.org/abs/2606.10728}
}