随着 AI 在全球范围内的普及，不同语言和文化背景的用户正将其应用于日常生活的更多场景中。通用型语言模型是强大的基础，但在面对特定应用时，它们往往缺乏本地知识、文化细微差别以及精确度。

上个月，团队里一个做了4年UI自动化的同事找我吐槽。他维护着800多条Playwright用例，那天早上打开报告一看——237条失败了。原因很简单：开发推了一次“不影响功能”的提交，把一批按钮的data-testid统一了命名规范。 他改定位器改到凌晨，第二天跟我说了一句话：“脚本写了这么多，为什么还是这么脆弱？” 我说：“因为你的定位规范、等待策略、踩过的坑，全部锁死在硬编码的代码里。AI读不懂 ...

摘要：针对移动应用自动化测试中脚本维护成本高、跨设备适配困难等问题，本文提出了一种基于多模态大模型的跨设备协同测试框架。该框架采用视觉理解与自然语言处理相结合的技术路线，破除了传统基于文档对象模型定位方法对页面结构的强依赖性，建立“视觉感知—语义理解 ...

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