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.

翻译：生成式人工智能（GenAI）正在迅速改变软件工程（SE）实践，影响着SE过程的执行方式以及软件系统的开发、运维与演进。本文应用设计科学研究方法，构建了GenAI增强型SE的发展路线图。该过程包含三个循环，逐步整合了多源证据，包括FSE 2025“软件工程2030”研讨会的协作讨论、快速文献综述以及同行参与的外部反馈会议。研究采用麦克卢汉的四元律作为概念工具，系统性地捕捉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增强的四种基本形式，并系统性地阐述了其相关的研究挑战与机遇。这些见解进而被整合为一组未来的研究方向。通过将路线图建立在严谨的多循环过程基础上，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，以及在这个快速发展的领域内规划未来研究，提供了透明且可复现的基础。