基于人工智能的设计系统感知开发：评估生产力和设计一致性
Design-System-Aware Development with AI: Evaluating Productivity and Design Consistency
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中文总结 AI 辅助
研究前端开发中从高保真原型转换界面的挑战，通过在巴西企业的对照实验，比较手动、仅DS及DS感知的AI辅助开发，发现AI辅助能显著加速开发、提高设计保真度，为工业前端工作流带来实际益处。
中文摘要 AI 辅助
设计系统（DS）有助于规范前端开发，但开发人员在将高保真原型转换为一致的、可投入生产的界面时仍面临挑战。尽管人工智能辅助工具已成为一种潜在解决方案，但在以DS为中心的工作流程中，关于其有效性的实证证据仍然有限。本文报告了在一家大型巴西企业进行的对照实验，该实验比较了手动开发、仅使用DS开发和DS感知的人工智能辅助开发在Angular、iOS和安卓平台上的情况。两个实验周期的结果表明，人工智能辅助显著缩短了交付时间（缩短了46.7%至69.4%），提高了任务完整性，并降低了性能变异性。对中断模式的分析进一步表明工作流程摩擦减少，任务执行更顺畅。这些发现提供了实证证据，表明DS感知的人工智能工具可以显著加速开发，提高设计保真度，并为工业前端工作流程带来实际好处。
英文摘要
Design Systems (DS) help standardize front-end development, yet developers still face challenges when translating high-fidelity mockups into consistent, production-ready interfaces. Although AI-assisted tools have emerged as a potential solution, empirical evidence on their effectiveness within DS-centered workflows remains limited. This paper reports a controlled experiment conducted at a large Brazilian enterprise that compares manual development, DS-only development, and DS-aware AI-assisted development across Angular, iOS, and Android stacks. Results from two experimental cycles show that AI assistance significantly reduced time-to-delivery (by 46.7% to 69.4%), increased task completeness, and decreased performance variability. Analysis of break patterns further suggests reduced workflow friction and smoother task execution. These findings provide empirical evidence that DS-aware AI tools can significantly accelerate development, improve design fidelity, and yield practical benefits for industrial front-end workflows.
