Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead

• URL: http://arxiv.org/abs/2504.04334v1
• Date: Sun, 06 Apr 2025 03:00:07 GMT
• Title: Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead
• Authors: Alessio Bucaioni, Martin Weyssow, Junda He, Yunbo Lyu, David Lo,
• Abstract summary: This paper presents a forward-looking vision for artificial intelligence-driven software architecture.<n>We examine how artificial intelligence can automate architectural design, support quantitative trade-off analyses, and continuously update architectural documentation.<n>The resulting roadmap outlines 14 current artificial intelligence contributions to software architecture, identifies six artificial intelligence-specific challenges in supporting architectural tasks, and reveals six avenues for future improvement.
• Score: 8.68898878009242
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents a forward-looking vision for artificial intelligence-driven software architecture that addresses longstanding challenges in design and evolution. Although artificial intelligence has achieved notable success in software engineering, its explicit application to software architecture remains under-explored. Traditional practices, heavily reliant on expert knowledge and complex trade-off reasoning, tend to be manual and error-prone, thereby compromising system quality and maintainability. Building on recent advances, we examine how artificial intelligence can automate architectural design, support quantitative trade-off analyses, and continuously update architectural documentation. Our approach combines a systematic review of state-of-the-art applications with insights from industry practitioners. The resulting roadmap outlines 14 current artificial intelligence contributions to software architecture, identifies six artificial intelligence-specific challenges in supporting architectural tasks, and reveals six avenues for future improvement, charting a course for future research and practical implementations.

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