---
name: role-aqa-mobile-testing-c11f061b4ecc
description: |
  Mobile test automation with Appium (cross-platform), Detox (React Native gray-box),
  XCUITest (iOS native), Espresso (Android native), device farms (BrowserStack,
  Sauce Labs, AWS Device Farm), screenshot testing, gesture testing, and deep link testing.
  Use when automating mobile app tests or setting up mobile test infrastructure.
allowed-tools: Read, Grep, Glob, Bash
---

# Mobile Testing

## When to use
- Choosing a mobile automation framework for a new project (Appium vs Detox vs native)
- Setting up a cloud device farm (BrowserStack, Sauce Labs, AWS Device Farm)
- Defining a device coverage matrix based on user analytics
- Writing gesture tests (swipe, pinch, long press, scroll) across screen sizes
- Testing deep links from cold start, warm start, and fresh install scenarios
- Setting up screenshot baseline testing for visual regression on mobile

## Core principles
1. **Gray-box beats black-box for React Native** — Detox synchronizes with app state; Appium polls; Detox wins on reliability
2. **Accessibility IDs over XPath** — XPath in Appium is the slowest locator strategy and breaks on layout changes
3. **Real devices for release validation, emulators for fast iteration** — emulators catch 80% of bugs at 10x speed
4. **Device matrix must reflect actual user analytics** — testing on devices nobody uses is wasted CI budget
5. **Deep links need cold start and warm start** — apps that only work warm are broken in half the entry scenarios

## Reference Files
- `references/frameworks-and-devices.md` — framework selection table, Appium capabilities setup, Detox gray-box pattern, XCUITest and Espresso notes, device farm comparison, device selection strategy
- `references/gestures-screenshots-deeplinks.md` — screenshot baseline testing, gesture scenarios (swipe/pinch/long press/scroll), deep link testing checklist covering cold start, warm start, universal links, and edge cases


---
Source attribution: rnavarych
Original project: https://github.com/rnavarych/alpha-engineer/blob/c5b74102c7fd584af3d344ba7c331a7bbec3c729/plugins/roles/role-aqa/skills/mobile-testing/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Raman Navarych

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: rnavarych
Original project: https://github.com/rnavarych/alpha-engineer/blob/c5b74102c7fd584af3d344ba7c331a7bbec3c729/plugins/roles/role-aqa/skills/mobile-testing/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering
Roles: DevOps / SRE, Mobile Developer, QA / Test Engineer
Specialties: Mobile, Testing
Tools: Appium, Aws Device Farm, Browserstack, Detox, Espresso, Sauce Labs, Xctest
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: d32cc3e27fbf08866a0868f69ee53f426248e5e013f009c24a28d086bf95de9c