2025/04/06 by Alessio Bucaioni, Martin Weyssow, Bucaioni, Alessio +7 · 1 citation
Computer Science · #Advanced Software Engineering Methodologies #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software Engineering Research #Software System Performance and Reliability
paper · pdf · doi:10.48550/arxiv.2504.04334
openalex publication_date 2025/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Artificial intelligence is increasingly applied across software engineering, yet its explicit role in software architecture remains insufficiently understood. Architectural practices rely on complex trade-offs, documentation, and long-term evolution, all of which are traditionally manual, error-prone, and difficult to sustain. To clarify how artificial intelligence can address these challenges, we conducted a systematic literature review of 51 peer-reviewed primary studies and systematically mapped their contributions onto 17 practitioner-reported software architecture challenges derived from empirical interviews. This analysis identifies 14 topical areas where artificial intelligence has been applied to architectural tasks and identifies six artificial intelligence-specific challenges that expose fundamental gaps between current capabilities and practitioner needs. Building on these findings, we chart a research agenda for artificial intelligence-driven software architecture organized around five strategic pillars. By grounding the roadmap in both systematic evidence and practitioner insights, this work provides the first peer-reviewed comprehensive synthesis of artificial intelligence contributions to software architecture, establishes a foundation for future research, and outlines the conditions under which artificial intelligence can become a trustworthy partner in architectural design, evaluation, and evolution.