# Linux Kernel Anti-Pattern Detector - Project Structure

## Overview

This project is organized into a clear, maintainable structure that separates concerns and makes it easy to find, modify, and extend functionality.

## Directory Structure

```
Linux Kernel Anti-Pattern Detector/
├── 📁 data/                          # Analysis data and results
│   ├── results.json                  # Main analysis results
│   ├── concurrency_analysis_report.json
│   └── kernel_analysis.log          # Analysis logs
│
├── 📁 docs/                          # Documentation
│   ├── kernel-analysis-guide.md     # Kernel analysis documentation
│   └── [additional documentation]
│
├── 📁 examples/                      # Example code and usage
│   └── [example files]
│
├── 📁 reports/                       # Generated analysis reports
│   ├── Linux_Kernel_Anti_Pattern_Analysis_Report.md
│   ├── Executive_Summary.md
│   └── 📁 concurrency/              # Concurrency-specific reports
│       └── Concurrency_Analysis_Report.md
│
├── 📁 scripts/                       # Analysis and utility scripts
│   ├── 📁 analysis/                 # Core analysis scripts
│   │   ├── concurrency_analyzer.py  # Concurrency issue analyzer
│   │   └── analyze_kernel_structure.py
│   ├── 📁 reporting/                # Report generation scripts
│   │   └── view_results.py         # Results viewer
│   └── 📁 utils/                    # Utility scripts
│       └── quick_summary.py        # Quick summary generator
│
├── 📁 src/                          # Source code (main project)
│   ├── __init__.py
│   ├── 📁 detectors/               # Anti-pattern detection modules
│   ├── 📁 rules/                   # Detection rules and patterns
│   └── 📁 utils/                   # Utility functions
│
├── 📁 tests/                        # Test files
│   └── [test files]
│
├── 📁 tools/                        # Analysis tools and detectors
│   ├── 📁 detectors/               # Main detection tools
│   │   ├── detector.py             # Main anti-pattern detector
│   │   └── config.yaml             # Detection configuration
│   ├── 📁 visualizers/             # Data visualization tools
│   └── 📁 exporters/               # Data export tools
│
├── 📁 linux/                        # Linux kernel source (cloned)
│   └── [kernel source files]
│
├── 📄 README.md                     # Main project documentation
├── 📄 requirements.txt              # Main project dependencies
├── 📄 requirements-kernel-analysis.txt
├── 📄 requirements-simple.txt
├── 📄 .gitignore                    # Git ignore rules
└── 📄 PROJECT_STRUCTURE.md          # This file
```

## Directory Descriptions

### 📁 data/
Contains all analysis results, logs, and generated data files.
- **results.json**: Complete analysis results from the main detector
- **concurrency_analysis_report.json**: Detailed concurrency analysis
- **kernel_analysis.log**: Analysis execution logs

### 📁 docs/
Project documentation and guides.
- **kernel-analysis-guide.md**: Comprehensive guide for kernel analysis
- Additional documentation for specific features

### 📁 examples/
Example code, usage patterns, and sample data.
- Example kernel modules for testing
- Sample configuration files
- Usage examples

### 📁 reports/
Generated analysis reports in various formats.
- **Linux_Kernel_Anti_Pattern_Analysis_Report.md**: Complete technical report
- **Executive_Summary.md**: High-level summary for stakeholders
- **concurrency/**: Specialized reports for specific issue types

### 📁 scripts/
Analysis and utility scripts organized by function.

#### 📁 analysis/
Core analysis scripts for different types of anti-patterns.
- **concurrency_analyzer.py**: Specialized concurrency issue analysis
- **analyze_kernel_structure.py**: Kernel structure analysis

#### 📁 reporting/
Scripts for generating and viewing reports.
- **view_results.py**: Interactive results viewer and reporter

#### 📁 utils/
Utility scripts for common tasks.
- **quick_summary.py**: Quick summary generation

### 📁 src/
Main project source code (core framework).
- **detectors/**: Anti-pattern detection modules
- **rules/**: Detection rules and pattern definitions
- **utils/**: Utility functions and helpers

### 📁 tests/
Test files and test data.
- Unit tests for detection modules
- Integration tests
- Test data and fixtures

### 📁 tools/
Analysis tools and detectors.

#### 📁 detectors/
Main detection tools and configurations.
- **detector.py**: Primary anti-pattern detection engine
- **config.yaml**: Detection configuration and rules

#### 📁 visualizers/
Data visualization and charting tools.
- Interactive dashboards
- Chart generators
- Data plotting utilities

#### 📁 exporters/
Data export and format conversion tools.
- JSON to other formats
- Report generation
- Data transformation

### 📁 linux/
Cloned Linux kernel source code for analysis.
- Complete kernel source tree
- Used for code snippet extraction
- Reference for pattern validation

## File Descriptions

### Core Files
- **README.md**: Main project documentation and getting started guide
- **requirements.txt**: Main project Python dependencies
- **requirements-kernel-analysis.txt**: Kernel analysis specific dependencies
- **requirements-simple.txt**: Simplified dependencies for basic usage
- **.gitignore**: Git ignore patterns for the project

### Configuration Files
- **tools/detectors/config.yaml**: Main detection configuration
- **tools/detectors/detector.py**: Primary detection engine

## Usage Patterns

### Running Analysis
```bash
# Main analysis
python tools/detectors/detector.py --clone --output data/results.json

# Concurrency analysis
python scripts/analysis/concurrency_analyzer.py

# View results
python scripts/reporting/view_results.py data/results.json
```

### Generating Reports
```bash
# Quick summary
python scripts/utils/quick_summary.py

# Interactive viewer
python scripts/reporting/view_results.py --interactive
```

### Development
```bash
# Install dependencies
pip install -r requirements.txt
pip install -r requirements-kernel-analysis.txt

# Run tests
python -m pytest tests/

# Development setup
conda activate linux-kernel-anti-pattern-detector
```

## Best Practices

### Adding New Features
1. **Analysis scripts**: Add to `scripts/analysis/`
2. **Reporting tools**: Add to `scripts/reporting/`
3. **Utilities**: Add to `scripts/utils/`
4. **Core detection**: Add to `src/detectors/`
5. **Configuration**: Update `tools/detectors/config.yaml`

### File Naming Conventions
- **Python files**: snake_case (e.g., `concurrency_analyzer.py`)
- **Configuration files**: kebab-case (e.g., `kernel-analysis-guide.md`)
- **Reports**: Pascal_Case (e.g., `Concurrency_Analysis_Report.md`)

### Data Management
- **Raw data**: Store in `data/`
- **Processed results**: Store in `data/`
- **Reports**: Generate in `reports/`
- **Logs**: Store in `data/`

## Maintenance

### Regular Tasks
1. **Update dependencies**: Review and update requirements files
2. **Clean data**: Remove old analysis results periodically
3. **Update kernel**: Refresh the Linux kernel source
4. **Backup reports**: Archive important analysis reports

### Version Control
- **Track**: Source code, configuration, documentation
- **Ignore**: Analysis results, logs, kernel source (large files)
- **Archive**: Important reports and findings

---

*This structure is designed to be scalable, maintainable, and easy to navigate. Each directory has a clear purpose and the organization supports both development and research workflows.*