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

Fulltext:


Authors:

Alessio Bucaioni, Martin Weyssow , Junda He , Yunbo Lyu , David Lo

Research groups:

Product and Production Development
Industrial AI Systems

Publication Type:

Conference/Workshop Paper

Venue:

2030 Software Engineering - 2025

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.

Bibtex

@inproceedings{Bucaioni7175,
author = {Alessio Bucaioni and Martin Weyssow and Junda He and Yunbo Lyu and David Lo},
title = {Artificial Intelligence for Software Architecture: Literature Review and the Road Ahead},
month = {June},
year = {2025},
booktitle = {2030 Software Engineering - 2025},
url = {http://www.ipr.mdu.se/publications/7175-}
}