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Design patterns are integral to software development, offering solutions to recurring design challenges. Detecting these patterns within code enhances comprehension, documentation, and maintenance. We review reported design pattern detection techniques based on supervised learning, feature-based analysis, clustering, graph-based methods, dynamic approaches, and ontology integration. We investigate the effectiveness of each technique and their strengths and limitations.

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A Review on Detection of Design Pattern in Source Code Using Machine Learning Techniques

  • 章节

  • 发表日期：

    2025年

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  • Sourav Biswas,
  • Meghavarshini Senthilkumar,
  • Jyoti Prakash Meher,
  • Rajib Mall

摘要

Design patterns are integral to software development, offering solutions to recurring design challenges. Detecting these patterns within code enhances comprehension, documentation, and maintenance. We review reported design pattern detection techniques based on supervised learning, feature-based analysis, clustering, graph-based methods, dynamic approaches, and ontology integration. We investigate the effectiveness of each technique and their strengths and limitations.