Attoflow Risk Assessment VS Code Extension

A VS Code extension that provides real-time code risk assessment for Python, JavaScript, and TypeScript files using machine learning models.

Features

• Real-time code analysis
• Support for multiple languages:
  • Python
  • JavaScript
  • TypeScript
• Risk level assessment (Low, Medium, High)
• Detailed recommendations for code improvement
• Visual indicators in the status bar
• Inline diagnostics for high-risk code

Requirements

• Python 3.8 or higher
• VS Code 1.60.0 or higher
• Required Python packages (installed automatically):
  • numpy
  • scikit-learn
  • joblib
  • pandas
  • xgboost
  • imbalanced-learn
  • esprima (for JavaScript/TypeScript parsing)

Installation

1. Install the extension from the VS Code marketplace
2. Install Python dependencies:

   pip install -r requirements.txt
   

3. Restart VS Code

Usage

The extension automatically analyzes Python, JavaScript, and TypeScript files as you type. You can also manually trigger analysis:

1. Open a supported file
2. Press Ctrl+Shift+P (Windows/Linux) or Cmd+Shift+P (Mac)
3. Type "Analyze Code Risk" and select the command

Status Bar Indicators

• 🟢 Low Risk
• 🟡 Medium Risk
• 🔴 High Risk

Configuration

The extension can be configured in VS Code settings:

• attoflowRiskAssessment.enable: Enable/disable real-time analysis
• attoflowRiskAssessment.updateInterval: Analysis update interval in milliseconds
• attoflowRiskAssessment.languages: List of languages to analyze (default: ["python", "javascript", "typescript"])

How It Works

1. The extension extracts features from your code:

   • Code complexity
   • Lines of code
   • Comment ratio
   • Nesting depth
   • Variable count
   • Function count
   • Class count
   • Import count
   • Exception count
   • Loop count

2. These features are analyzed by multiple ML models:

   • Random Forest
   • SVM
   • XGBoost

3. The models' predictions are combined to provide:

   • Overall risk level
   • Probability of defects
   • Language-specific recommendations

Language-Specific Features

Python

• AST-based analysis
• Python-specific complexity metrics
• PEP 8 style recommendations

JavaScript/TypeScript

• Esprima-based parsing
• Modern JS/TS features support
• Recommendations for:
  • Object destructuring
  • Array methods
  • Higher-order functions
  • Async/await patterns

Development

Building from Source

1. Clone the repository
2. Install dependencies:

   npm install
   pip install -r requirements.txt
   

3. Build the extension:

   npm run compile
   

Running Tests

python -m unittest discover tests

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

License

MIT