Automating Software Design with AI: A Deep Learning Approach to Design Pattern Recognition
Abstract
Artificial intelligence (AI) has made significant strides in automating various aspects of software development, and one such area is software design. This paper explores the application of deep learning techniques for automating design pattern recognition in software engineering. By training neural networks on large codebases, the system can automatically identify and suggest appropriate design patterns based on the structure and behavior of the code. The paper discusses the potential benefits of AI in enhancing design quality, reducing human error, and speeding up the software development process. It also addresses challenges such as the need for large labeled datasets and the interpretability of AI-driven suggestions. The research includes case studies that demonstrate the practical use of deep learning models in design pattern identification and their impact on improving software design processes.
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