Socratic-SWE: Self-Evolving Coding Agents via Trace-Derived Agent Skills
LLM-driven software engineering agents have become a central testbed for real-world language-model capability, yet their training remains limited by the availability of high-quality SWE tasks. Existing synthetic data methods typically create tasks through fixed mutation or bug-injection procedures, making the resulting distributions largely independent of the agent's own weaknesses and training progress. We introduce Socratic-SWE, a closed-loop self-evolution framework that reuses the agent's historical solving traces as a source of training signal. Rather than treating traces only as evidence for reward computation, Socratic-SWE distills them into structured agent skills that summarize r...
| Authors | Chuan Xiao, Zhengbo Jiao, Shaobo Wang et al. |
|---|---|
| Primary category | cs.SE |
| Published | 5 June 2026 |
| Last updated at source | 5 June 2026 |
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