LLM-assisted approach recovers ROS~2 system architecture

Researchers have developed a new method for recovering software architecture from complex ROS~2 systems using Large Language Models (LLMs). This approach refines LLM prompting for better consistency and introduces a staged recovery strategy with multi-level intermediate representations. The enhanced pipeline was evaluated on a challenging real-world robotic system, demonstrating improved structural consistency, scalability, and robustness in architecture reconstruction. AI

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IMPACT Enhances software engineering practices for complex robotic systems by improving architecture recovery.

RANK_REASON The cluster contains an academic paper detailing a new methodology for software architecture recovery. [lever_c_demoted from research: ic=1 ai=1.0]

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• Dominique Briechle
• Large Language Models
• ROS~2

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