daVinci-Env: Open SWE Environment Synthesis at Scale
Training capable software engineering (SWE) agents demands large-scale, executable, and verifiable environments that provide dynamic feedback loops for iterative code editing, test execution, and solution refinement. However, existing open-source datasets remain limited in scale and repository diversity, while industrial solutions are opaque with unreleased infrastructure, creating a prohibitive barrier for most academic research groups. We present OpenSWE, the largest fully transparent framework for SWE agent training in Python, comprising 45,320 executable Docker environments spanning over 12.8k repositories, with all Dockerfiles, evaluation scripts, and infrastructure fully open-source...
| Authors | Dayuan Fu, Shenyu Wu, Yunze Wu et al. |
|---|---|
| Primary category | cs.SE |
| Published | 13 March 2026 |
| Last updated at source | 16 March 2026 |
Connected in the knowledge graph
- ritvik-sarvam/openswe-harborDataset · cited by
- GAIR/OpenSWEDataset · cited by
Models and datasets referencing this paper
- GAIR/OpenSWEDataset
- ritvik-sarvam/openswe-harborDataset
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