录制、生成、运行：AI 驱动的 iOS UI 测试生成

Introduction

介绍

In our recent AutoTrack SDK blog post, we shared how we solved the challenge of capturing complete user journeys across our mobile app. One of the most promising applications we highlighted was automating iOS UI (User Interface) test case generation using the rich interaction data to automatically create test scripts that mimic real-world usage patterns.

在我们最近的 AutoTrack SDK 博客文章中，我们分享了如何解决捕捉移动应用中完整用户旅程的挑战。我们突出展示的最有前景的应用之一是使用丰富的交互数据自动化 iOS UI（User Interface）测试用例生成，自动创建模仿真实世界使用模式的测试脚本。

Our vision has become a reality with the development of the Mobile UI Testing AI Workflow for iOS. This system lets developers record their interactions with the app and, within minutes, receive complete, executable UI test code. This code includes essential components such as mocks, feature flags, and analytics verification. In this post, we will explore how we brought this system to life, the architecture we selected, and the valuable lessons we learned throughout the process.

我们的愿景随着Mobile UI Testing AI Workflow for iOS.的开发而成为现实。这个系统让开发者记录他们与应用的交互，并在几分钟内接收完整、可执行的 UI 测试代码。此代码包括模拟对象、特性标志和分析验证等基本组件。在本文中，我们将探讨我们如何将这个系统变为现实、我们选择的架构，以及我们在整个过程中学到的宝贵经验。

The problem: UI tests are expensive to write

问题：编写 UI 测试成本高

Writing UI tests manually is time-consuming and repetitive. Developers typically spend days:

手动编写 UI 测试很耗时且重复。开发人员通常需要花费数天：

• Writing test code line by line.
• 逐行编写测试代码。
• Creating mock data and API responses.
• 创建 mock 数据和 API 响应。
• Configuring feature flags and test environments.
• 配置功能标志和测试环境。
• Maintaining tests when the UI changes.
• UI 变更时维护测试。

Even more concerning is that this effort often leads to incomplete coverage. Teams prioritise critical flows and leave edge cases untested. When bugs surface in production, reproducing them requires piecing together user journeys from fragmented data, which is exactly the problem AutoTrack was designed to solve.

更令人担忧的是，这种努力往往导致不完整覆盖。团队优先处理关键流程，忽略边缘情况。当 bug 在生产环境中出现时，重现它们需要从碎片化数据中拼凑用户旅程，这正是 AutoTrack 旨在解决的问题。

This prompts us to ask: What if we could turn AutoTrack’s recorded user journeys...