MaaXYZ/MaaFramework

基于图像识别的自动化黑盒测试框架 | An automation black-box testing framework based on image recognition

What it solves

It provides a standardized, low-code framework for creating automated black-box testing programs. It specifically addresses the difficulty of automating interactions with software where internal APIs are unavailable, allowing developers to build automation tools based on visual cues rather than internal code access.

How it works

The framework uses image recognition technology to identify elements on a screen and simulate user controls. It employs a "Pipeline" low-code protocol and a Project Interface (PI) protocol to allow developers to define automation sequences and tasks with minimal coding while maintaining high extensibility.

Who it’s for

It is designed for developers who want to build black-box automation tools, such as game assistants or software testers, across multiple platforms including Windows, Linux, macOS, and Android.

Highlights

  • Multi-Language Support: Provides bindings and integration for C++, Python, Node.js, Go, and Rust.
  • Cross-Platform: Works across Windows, Linux, macOS, and Android.
  • Low-Code Approach: Uses a pipeline protocol to simplify the creation of complex automation workflows.
  • Extensive Ecosystem: Supported by a wide array of community-built GUIs, debuggers, and visual pipeline editors.

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