Author

Junyi Zhu

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Open access Jul 2026

Repairing Docker Smells with Large Language Models: An Empirical Study

A novel Detect–Guide–Repair (DGR) framework is proposed, which integrates rule-based smell detection with a context-aware repair mechanism driven by large language models (LLMs), enabling a more flexible and intelligent automated repair process for Docker smell repair.

Chenhui Zhang, Haiyan Wang, Junyi Zhu et al. · Applied Sciences · 0 citations

Open access Aug 2026

L-ARLPT: An LLM-Augmented Reinforcement Learning Framework for Autonomous Penetration Testing

A Large Language Model-enhanced Autonomous Reinforcement Learning Penetration Testing framework that leverages the domain knowledge embedded in a Large Language Model to perform tactical planning, thereby pruning the original action space into a compact set of candidate actions.

Rufeng Zhan, Junyi Zhu, Yinghui Xu et al. · Applied Sciences · 0 citations