This research introduces a novel LLM-based approach to automatically identify software design patterns in codebases, addressing limitations of traditional static analysis tools.

• Leverages LLMs to recognize complex pattern implementations across diverse codebases
• Helps developers quickly understand unfamiliar code structure and architecture
• Improves software quality and maintainability through better pattern recognition
• Overcomes challenges of variability and lack of explicit pattern annotations

For engineering teams, this represents a significant advancement in automated code comprehension tools, potentially reducing onboarding time for new developers and supporting better software maintenance practices.

LLM-Based Design Pattern Detection