Generative AI (GenAI) is rapidly transforming software engineering (SE) practices, influencing how SE processes are executed, as well as how software systems are developed, operated, and evolved. This paper applies design science research to build a roadmap for GenAI-augmented SE. The process consists of three cycles that incrementally integrate multiple sources of evidence, including collaborative discussions from the FSE 2025 "Software Engineering 2030" workshop, rapid literature reviews, and external feedback sessions involving peers. McLuhan's tetrads were used as a conceptual instrument to systematically capture the transforming effects of GenAI on SE processes and software products.The resulting roadmap identifies four fundamental forms of GenAI augmentation in SE and systematically characterizes their related research challenges and opportunities. These insights are then consolidated into a set of future research directions. By grounding the roadmap in a rigorous multi-cycle process and cross-validating it among independent author teams and peers, the study provides a transparent and reproducible foundation for analyzing how GenAI affects SE processes, methods and tools, and for framing future research within this rapidly evolving area. Based on these findings, the article finally makes ten predictions for SE in the year 2030.

翻译：生成式人工智能（GenAI）正迅速变革软件工程（SE）实践，深刻影响着SE过程的执行方式以及软件系统的开发、运维与演化模式。本文运用设计科学研究方法，构建了GenAI增强型SE的发展路线图。该研究过程包含三个迭代循环，逐步整合了多源证据，包括FSE 2025“2030年软件工程”研讨会的协作讨论、快速文献综述，以及涵盖同行评审的外部反馈会议。研究采用麦克卢汉四元律作为概念工具，系统捕捉了GenAI对SE过程及软件产品的变革性影响。最终形成的路线图识别了SE中GenAI增强的四种基本形态，并系统阐述了其相关的研究挑战与机遇。这些发现被整合为一组未来研究方向。通过将路线图建立在严谨的多循环研究过程中，并在独立作者团队与同行间进行交叉验证，本研究为分析GenAI如何影响SE过程、方法与工具提供了透明且可复现的基础框架，并为这一快速演进领域的未来研究确立了范式。基于上述研究成果，本文最终提出了针对2030年软件工程领域的十项预测。