MoAutoPilot

MoAutoPilot is a mobile automation testing framework based on Appium, supporting Android, iOS, and HarmonyOS platforms, with integrated AI-driven test case generation capabilities.

✨ Features

• 🌈 Multi-platform Support
  • Android devices and emulators
  • iOS devices and emulators
  • HarmonyOS devices
• 🎯 Intelligent Testing
  • Smart element location
  • Automatic waiting and retry
  • Automatic permission dialog handling
• 🔄 Parallel Testing
  • Multi-device parallel execution
  • Failure retry mechanism
  • Test case priority management
• 📊 Test Reports
  • HTML format reports
  • Failed scenario screenshots
  • Detailed execution logs
• 🤖 AI-driven Testing
  • LLM-based test case generation
  • Intelligent UI analysis and interaction
  • Adaptive testing strategies

🔍 Differences from Other Automation Testing Frameworks

MoAutoPilot has made several innovations based on traditional mobile automation testing frameworks:

Feature	MoAutoPilot	Traditional Automation Frameworks
Test Case Generation	AI-driven automatic generation	Manual writing
Element Location	Intelligent location, multiple strategies with automatic switching	Fixed location strategies
Platform Support	Android, iOS, HarmonyOS	Usually only Android and iOS
Testing Strategy	Adaptive testing strategies based on AI analysis	Fixed testing strategies
Maintenance Cost	Low (automatically adapts to UI changes)	High (UI changes require manual updates)
Test Coverage	High (AI can explore edge cases)	Medium (only covers predefined scenarios)
Execution Efficiency	High (parallel execution, intelligent retry)	Medium (regular execution strategies)

Core Advantages

1. AI-driven Test Case Generation: No need to manually write numerous test cases, AI can automatically generate comprehensive test scenarios based on application descriptions
2. Intelligent UI Analysis: Automatically analyze application interface structure, identify key interactive elements
3. Cross-platform Compatibility: One framework supports all three major mobile platforms, including the emerging HarmonyOS
4. Adaptive Test Execution: Dynamically adjust testing strategies based on test results, improving testing efficiency
5. Low Maintenance Cost: Automatically adapt to UI changes, reducing maintenance workload

🚀 Quick Start

Requirements

• Python 3.8+
• Node.js 18/20
• Java JDK 8
• Android SDK (for Android testing)
• Xcode (for iOS testing)
• Appium 2.0+
• Ollama (for AI test case generation)

Installation Steps

1. Clone the project and install dependencies

git clone https://github.com/yourusername/MoAutoPilot.git
cd MoAutoPilot
python -m venv venv
source venv/bin/activate  # macOS/Linux
# or
.\venv\Scripts\activate   # Windows
pip install -r requirements.txt

2. Install Ollama (for AI test case generation)

# macOS
curl -fsSL https://ollama.com/install.sh | sh

# Linux
curl -fsSL https://ollama.com/install.sh | sh

# Windows
# Download the installer from https://ollama.com/download

3. Download LLM model (recommended to use deepseek series models)

ollama pull deepseek-r1:8b
# or use a larger parameter model for better results
ollama pull deepseek-r1:14b

4. Configure the test environment

# Check environment configuration
python -m pytest tests/test_environment.py -v -s

5. Configure device information

# config/config.yaml
devices:
  android:
    - deviceName: "Pixel_4"
      platformVersion: "11.0"
      app: "~/apps/demo.apk"

  ios:
    - deviceName: "iPhone 12"
      platformVersion: "14.5"
      app: "~/apps/demo.ipa"

  harmony:
    - platformName: HarmonyOS
      deviceName: Harmony Device
      platformVersion: '2.0'
      automationName: UiAutomator2
      appPackage: com.example.harmonyapp
      appActivity: .MainActivity
      noReset: true

🤖 AI Test Case Generation

MoAutoPilot integrates test case generation functionality based on large language models, which can automatically generate test cases according to application descriptions.

Configure AI Test Case Generation

1. Ensure the Ollama service is running

# Check Ollama service status
curl http://localhost:11434/api/tags

2. Prepare test case description file

Create a Markdown file in the test_cases_source directory, describing the application functionality and testing requirements:

# Short Video Application Testing Requirements

## Functional Description
The short video application allows users to browse, upload, edit, and share short video content.

## Testing Scope
- Video browsing functionality
- Video upload functionality
- User interaction functionality (like, comment, share)
- Account management functionality

Generate Test Cases

Run the test case generation script:

python -m pytest test_cases/test_automation.py::TestAutomation::load_test_cases_from_source -v -s

Generated test cases will be saved in the gen_cases directory, in JSON or Markdown format.

Customize AI Prompt Templates

You can customize AI prompt templates according to your needs to generate test cases that better meet specific requirements:

# Modify the prompt template in test_automation.py
prompt = f"""You are an expert focused on mobile APP testing, please generate test cases for {app_type} APP features, output in JSON format:\
            {content}
            Requirements include: test steps, expected results, priority.
            Special attention:
                1. {specific_focus_point1}
                2. {specific_focus_point2}
                3. {specific_focus_point3}"""

Using LangChain Framework (Optional)

MoAutoPilot also supports using the LangChain framework for more flexible AI test case generation:

from langchain.prompts import PromptTemplate
from langchain_community.llms import Ollama

template = """As a senior test engineer, please generate test cases for {feature}:
1. Include {normal_count} normal scenarios and {error_count} error scenarios
2. Each case needs clear preconditions
3. Output in Markdown table format"""

prompt = PromptTemplate.from_template(template)
llm = Ollama(model="deepseek-r1:14b", temperature=0.5)

chain = prompt | llm
response = chain.invoke({
    "feature": "TikTok video upload functionality",
    "normal_count": 3,
    "error_count": 2
})

📝 Usage Examples

Test Case Writing

from utils.appium_driver import AppiumDriver
from pages.login_page import LoginPage

def test_login():
    # Initialize driver
    driver = AppiumDriver(platform='android')
    
    # Perform login operation
    login_page = LoginPage(driver)
    login_page.login("username", "password")
    
    # Verify results
    assert login_page.is_login_successful()

Page Object Definition

from utils.base_page import BasePage

class LoginPage(BasePage):
    # Page elements
    username_input = "id=username"
    password_input = "id=password"
    login_button = "id=login"
    
    def login(self, username, password):
        self.input_text(self.username_input, username)
        self.input_text(self.password_input, password)
        self.click(self.login_button)

Running Tests

# Run a single test
pytest test_cases/test_automation.py -v -s

# Parallel testing
pytest test_cases/ -n auto

# Generate report
pytest test_cases/ --html=report.html

🤝 Contribution

Issues and Pull Requests are welcome.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details

HarmonyOS Support

MoAutoPilot supports automated testing of HarmonyOS devices. To test HarmonyOS devices, ensure:

1. Developer mode is enabled on the device
2. Necessary drivers are installed
3. HarmonyOS device information is configured in config/config.yaml

Example configuration:

harmony:
  platformName: HarmonyOS
  deviceName: Harmony Device
  platformVersion: '2.0'
  automationName: UiAutomator2
  appPackage: com.example.harmonyapp
  appActivity: .MainActivity
  noReset: true

When running tests, set the environment variable:

export TEST_PLATFORM=harmony
pytest test_cases/test_automation.py