English(EN) Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction

LLM辅助方法恢复ROS~2系统架构

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-19 16:14

研究人员开发了一种新方法，利用大型语言模型（LLMs）从复杂的ROS~2系统中恢复软件架构。该方法改进了LLM提示以获得更好的一致性，并引入了一种分阶段恢复策略，包含多层次的中间表示。该增强的流程在一个具有挑战性的真实机器人系统上进行了评估，证明了在架构重构方面提高了结构一致性、可扩展性和鲁棒性。 AI

影响通过改进架构恢复来增强复杂机器人系统的软件工程实践。

排序理由该集群包含一篇学术论文，详细介绍了软件架构恢复的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Meng Zhang · 2026-05-19 16:14

Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction

Explicit software architecture models are essential artifacts for communicating, analyzing, and evolving complex software-intensive systems. In ROS~2-based robotic systems, however, structural (de-)composition and integration semantics are often only implicitly encoded across dis…

报道来源 [1]

Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction

相关实体

相关话题