stack-performance/README.md

A comprehensive application stack analyzer that evaluates MEAN, MERN, and other Node.js-based applications across 15 performance criteria

# Stack Performance Analyzer

A comprehensive Node.js application stack analyzer that evaluates MEAN, MERN, and other Node.js-based applications across 15 performance criteria using sophisticated algorithms rather than random scoring.

## Features

🔍 **Comprehensive Analysis**: Evaluates applications across 15 key performance criteria:

1. **Application Performance** - Framework efficiency, code structure, caching  
2. **Developer Productivity** - Tooling support, learning curve, community  
3. **API Response Time** - Framework efficiency, database optimization  
4. **Learning Curve** - Documentation quality, complexity assessment  
5. **Security Features** - Authentication, validation, vulnerability analysis  
6. **Tooling & Ecosystem Support** - Development tools integration  
7. **Integration with MongoDB** - Database connectivity and optimization  
8. **Modularity & Scalability** - Code organization and scalability patterns  
9. **Package Ecosystem** - Dependency management and quality  
10. **Startup Time** - Application bootstrap performance  
11. **Maintenance and Debugging** - Code maintainability metrics  
12. **Hosting and Deployment Flexibility** - Deployment options assessment  
13. **Memory & CPU Efficiency** - Resource utilization analysis  
14. **Performance under Concurrent Load** - Scalability assessment  
15. **Monitoring and Observability** - Logging and monitoring capabilities  

🎯 **Algorithmic Scoring**: Uses sophisticated algorithms to analyze:
- Code complexity and patterns
- Dependency analysis
- Framework characteristics
- Security implementations
- Performance optimizations

📊 **Detailed Reporting**: Provides:
- Individual criterion scores (0–100)
- Performance remarks (Excellent, Best, Good, Average, Poor)
- Overall weighted score
- Specific recommendations for improvement
- Stack detection (MEAN, MERN, Express.js, etc.)

## Installation

```bash
# Install dependencies
npm install

# (Optional) Make CLI globally available
npm link

# Add the following script in your project's package.json
# so you can run the analyzer with npm

# Inside package.json
"scripts": {
  "analyze": "node node_modules/stack-performance-analyzer/index.js"
}


## Usage

### Command Line Interface
# Analyze current directory using CLI directly
node node_modules/stack-performance-analyzer/index.js

# Analyze specific project
node node_modules/stack-performance-analyzer/index.js /path/to/your/project

# Save results to JSON file
node node_modules/stack-performance-analyzer/index.js . --save results.json

# Show verbose output
node node_modules/stack-performance-analyzer/index.js . --verbose

# Output as JSON
node node_modules/stack-performance-analyzer/index.js . --output json

```

### Using npm script 
After adding the "analyze" script to your package.json, run:

# Runs the analyzer using npm script
npm run analyze


### Programmatic Usage

```javascript
const ApplicationAnalyzer = require('./index');

const analyzer = new ApplicationAnalyzer({
  projectPath: '/path/to/project'
});

analyzer.analyze()
  .then(results => {
    console.log('Analysis complete!');
    console.log('Overall Score:', results.overall.score);
    console.log('Performance:', results.overall.remark);
    
    // Individual criterion results
    results.criteria.forEach(criterion => {
      console.log(`${criterion.name}: ${criterion.score}/100 (${criterion.remark})`);
    });
  })
  .catch(error => {
    console.error('Analysis failed:', error);
  });
```

## How It Works

### Algorithmic Approach

This analyzer uses **sophisticated algorithms** rather than random number generation:

1. **Stack Detection**: Analyzes `package.json` to identify technology stack
2. **Weighted Scoring**: Each criterion has specific weight based on importance
3. **Multi-Factor Analysis**: Each criterion evaluates multiple factors:
   - Code structure and complexity
   - Dependency analysis
   - Configuration file analysis
   - Best practice pattern detection
   - Security implementation analysis

### Example Analysis Process

**Application Performance (12% weight)**:
- Framework Performance (30%): Analyzes framework choice and characteristics
- Code Structure (25%): Evaluates code complexity and patterns
- Database Integration (20%): Checks for optimization patterns
- Asset Management (15%): Build tools and optimization
- Caching Implementation (10%): Caching strategy analysis

**Security Features (9% weight)**:
- Authentication (30%): JWT, Passport, session management
- Data Validation (25%): Input validation libraries and patterns
- Security Headers (20%): Helmet, CORS implementation
- Vulnerability Assessment (25%): Dependency security analysis

## Sample Output

```
📊 STACK PERFORMANCE ANALYSIS RESULTS
============================================================
Application Performance          |  87/100 | Best
Developer Productivity           |  92/100 | Excellent  
API Response Time               |  78/100 | Good
Learning Curve                  |  85/100 | Best
Security Features               |  71/100 | Good
Tooling & Ecosystem Support     |  88/100 | Best
Integration with MongoDB        |  82/100 | Best
Modularity & Scalability        |  76/100 | Good
Package Ecosystem              |  84/100 | Best
Startup Time                   |  73/100 | Good
Maintenance and Debugging      |  79/100 | Good
Hosting and Deployment         |  81/100 | Best
Memory & CPU Efficiency        |  75/100 | Good
Performance under Load         |  77/100 | Good
Monitoring and Observability   |  69/100 | Average
------------------------------------------------------------
OVERALL PERFORMANCE            |  80/100 | Best

✅ Analysis Complete

🔧 Detected Stack Information:
Stack Type: MERN
Technologies: MongoDB, Express.js, React, Node.js
Node.js Version: 18.17.0
```

## Supported Stacks

- **MEAN Stack** (MongoDB, Express.js, Angular, Node.js)
- **MERN Stack** (MongoDB, Express.js, React, Node.js)
- **Express.js Applications**
- **Fastify Applications**
- **Koa Applications**
- **React Applications**
- **Vue.js Applications**
- **Generic Node.js Applications**

## Architecture

```
├── analyzers/           # Individual criterion analyzers
│   ├── BaseAnalyzer.js  # Base class with common functionality
│   ├── ApplicationPerformanceAnalyzer.js
│   ├── DeveloperProductivityAnalyzer.js
│   └── ... (15 total analyzers)
├── lib/
│   └── StackAnalyzer.js # Main analyzer coordination
├── bin/
│   └── cli.js          # Command line interface
├── index.js            # Main entry point
└── package.json        # Project configuration
```

## Contributing

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request

## License

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

## Changelog

### v1.0.0
- Initial release with 15 comprehensive analysis criteria
- Algorithmic scoring system (no random numbers)
- Support for major Node.js stacks (MEAN, MERN, etc.)
- CLI and programmatic interfaces
- Detailed reporting with recommendations
### AUTHOR
Gugan M K