arXiv:2511.01348cs.SEcs.AI2025-11中稿 · the 2nd IEEE/ACM I…被引 8

欧洲GENIUS项目勾勒生成式AI在软件工程全周期的应用蓝图

The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Project

  • 整合30余家产学研机构,系统梳理生成式AI在开发全周期的挑战
  • 提出未来五年关键技术与方法演进方向,推动工具落地与工业验证
  • 关注可靠性与安全,助力开发者角色转型与产业协同

生成式AI(GenAI)已成为软件工程领域的突破性力量,能够生成代码、识别缺陷、推荐修复方案并支持质量保障。尽管其在编码任务中展现出巨大潜力,但将GenAI全面应用于整个软件开发生命周期(SDLC)尚未充分探索。在可靠性、问责制、安全性和数据隐私等关键领域仍存在重大不确定性,亟需深入研究与协同应对。欧洲GENIUS项目汇聚超过30家工业与学术机构,致力于推进AI在所有SDLC阶段的融合。该项目聚焦于GenAI的潜力、创新工具开发及新兴研究挑战,积极塑造软件工程的未来。本文基于跨领域对话及项目内部经验,提出对生成式AI驱动软件工程未来的共同愿景,涵盖四个核心维度:(1)系统梳理当前GenAI在SDLC各阶段应用中的主要挑战;(2)展望未来五年内预期的关键技术与方法进步;(3)预测软件专业人员角色演变与技能需求变化;(4)阐述GENIUS项目通过实用工具与工业验证推动转型的具体贡献。本文强调技术革新与商业价值的协同,旨在为科研议程与企业战略提供指导,奠定可信赖、可扩展、面向产业的生成式AI解决方案基础。

原文摘要 · Abstract (English)

Generative AI (GenAI) has recently emerged as a groundbreaking force in Software Engineering, capable of generating code, identifying bugs, recommending fixes, and supporting quality assurance. While its use in coding tasks shows considerable promise, applying GenAI across the entire Software Development Life Cycle (SDLC) has not yet been fully explored. Critical uncertainties in areas such as reliability, accountability, security, and data privacy demand deeper investigation and coordinated action. The GENIUS project, comprising over 30 European industrial and academic partners, aims to address these challenges by advancing AI integration across all SDLC phases. It focuses on GenAI's potential, the development of innovative tools, and emerging research challenges, actively shaping the future of software engineering. This vision paper presents a shared perspective on the future of GenAI-driven software engineering, grounded in cross-sector dialogue as well as experiences and findings within the GENIUS consortium. The paper explores four central elements: (1) a structured overview of current challenges in GenAI adoption across the SDLC; (2) a forward-looking vision outlining key technological and methodological advances expected over the next five years; (3) anticipated shifts in the roles and required skill sets of software professionals; and (4) the contribution of GENIUS in realising this transformation through practical tools and industrial validation. This paper focuses on aligning technical innovation with business relevance. It aims to inform both research agendas and industrial strategies, providing a foundation for reliable, scalable, and industry-ready GenAI solutions for software engineering teams.

生成式AI软件工程工业合作未来展望

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