AI-Driven Software Design Patterns: Automation in System Architecture
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I1P109Keywords:
Software Design Patterns, Machine Learning, Explainable AI, Automation, AI-DrivenAbstract
Modern software systems have been growing in their complexity and thus require novel methods of design and architecture. Software design patterns have long been an effective way of dealing with design problems, the main drawback being that they are very manual and require the expertise of the application. Rapid improvements in Artificial Intelligence (AI) provide new possibilities to automate the process of recognizing, suggesting, and adapting software design patterns effectively, which results in the overall improvement of development. In this paper, a new, entire AI-based framework is proposed based on Machine Learning (ML), Natural Language Processing (NLP), and deep neural networks to automate the application of design patterns in the system design. The framework is fully integrated into development environments, allowing for real-time pattern suggestions, adaptive code refactoring, and automatic code generation. A prototype has also been developed that shows the system to be able to understand source code, detect excerpts of anti-patterns, and suggest the best possible design components in various areas of development. The proposed system shows high gains in accuracy, productivity, and the quality of the code based on a large number of experiments and subjective reports of developers. Challenges such as model generalisation, limitations of dataset size, and explainability are critically examined, and strategies to address these challenges in the future are proposed to enhance transparency and interoperability. This will enable an automated decision-making process for repetitive design areas and facilitate the integration of AI within the architectural process, leading to the development of the first generation of smart tools. It highlights how AI has the potential to transform the principles of software architecture, enabling accelerated innovation and practical systems for maintenance
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