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About this paper
Jiaran Zhang, Luck Ma, Fanqi Wan, Di Qi, Xu Zhao, Jieyi Hou, Zhe Xie, Mengqiang Ren and 5 more
DOCKSMITH is an agentic Docker builder framework that enhances the reliability of environment construction for software engineering agents by treating it as a core agentic capability. It achieves a 39.72% Fail-to-Pass rate on Multi-Docker-Eval, outperforming baselines, and demonstrates that specialized training in Docker building improves general agentic performance on tasks like SWE-bench.
Key insights
- Environment construction can be reconceptualized as a core agentic capability involving complex reasoning, iterative tool use, and failure recovery, providing transferable supervision signals for broader agentic software engineering tasks.
- Joint training with general software engineering data (e.g., SWE-solving trajectories) and strategic curriculum sampling significantly improve both Docker-building reliability and the transferability of learned skills.
- The systematic filtering of unproductive trajectories and complexity-based curriculum sampling are crucial for creating a high-signal training corpus and improving an agent's ability to handle challenging environment builds.
Summary by alphaXiv.
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