Add C++ detector with GPU acceleration and GUI

README.md

@@ -10,10 +10,32 @@
 
 How can we develop zero-shot detection of machine generated codes? Welcome to the repository for the research paper: **"Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers."** Our paper has been accepted to the 47th International Conference on Software Engineering (**ICSE 2025**).
 
+## NEW: C++ Edition with GUI
+
+We've created an enhanced version of DetectCodeGPT specifically for analyzing C++ projects! Features include:
+
+- 🚀 **GPU Acceleration**: Automatic GPU detection (CUDA/MPS) for faster processing
+- 🖥️ **User-Friendly GUI**: Intuitive interface for configuration and monitoring
+- 📁 **Multi-Project Support**: Scan entire directories with multiple C++ projects
+- 📊 **Comprehensive Reporting**: JSON output with detailed scores and human-readable reports
+- ⚡ **CLI Mode**: Command-line interface for automation
+
+**Quick Start:**
+
+```bash
+cd cpp-detector
+python main_app.py  # Launch GUI
+# OR
+python main_app.py --cli --directory /path/to/cpp/projects  # CLI mode
+```
+
+See [cpp-detector/README.md](cpp-detector/README.md) for detailed documentation.
+
 ## Table of Contents
 
 - [DetectCodeGPT](#detectcodegpt)
   - [Table of Contents](#table-of-contents)
+  - [NEW: C++ Edition with GUI](#new-c-edition-with-gui)
   - [Getting Started](#getting-started)
     - [Prerequisites](#prerequisites)
     - [Data Preparation](#data-preparation)

cpp-detector/README.md

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+# DetectCodeGPT C++ Edition
+
+An enhanced version of DetectCodeGPT specifically designed to detect AI-generated C++ code across multiple projects. Features GPU acceleration, a user-friendly GUI, and comprehensive JSON reporting.
+
+## Features
+
+- **Multi-Project Support**: Scan entire directories containing multiple C++ projects
+- **GPU Acceleration**: Automatically detects and uses available GPUs (CUDA, MPS) for faster processing
+- **User-Friendly GUI**: Intuitive interface for configuration and real-time progress monitoring
+- **CLI Mode**: Command-line interface for automation and scripting
+- **Comprehensive Output**: JSON results with detailed scores and human-readable reports
+- **Flexible Configuration**: Customizable detection parameters and model selection
+
+## Installation
+
+### Prerequisites
+
+- Python 3.9.7 or higher
+- CUDA-capable GPU (optional, but recommended for better performance)
+
+### Install Dependencies
+
+From the repository root:
+
+```bash
+pip install -r requirements.txt
+```
+
+Or install specific requirements for the C++ detector:
+
+```bash
+cd cpp-detector
+pip install -r requirements.txt
+```
+
+## Usage
+
+### GUI Mode (Recommended)
+
+Launch the graphical interface:
+
+```bash
+cd cpp-detector
+python main_app.py
+```
+
+The GUI provides:
+- **Configuration Tab**: Set up directories, models, and detection parameters
+- **Processing Tab**: Monitor real-time progress and logs
+- **Results Tab**: View detection results and export reports
+
+### CLI Mode
+
+For automation or headless environments:
+
+```bash
+# Basic usage
+python main_app.py --cli --directory /path/to/cpp/projects
+
+# With custom settings
+python main_app.py --cli \
+    --directory /path/to/cpp/projects \
+    --output results.json \
+    --report report.txt \
+    --n-perturbations 100 \
+    --device cuda
+
+# Show available devices
+python main_app.py --device-info
+```
+
+### CLI Options
+
+```
+--cli                    Run in CLI mode instead of GUI
+--directory, -d          Directory to scan for C++ files (required for CLI)
+--output, -o             Output JSON file path
+--report, -r             Generate text report at specified path
+--base-model             Base model for scoring (default: codellama/CodeLlama-7b-hf)
+--mask-model             Mask filling model (default: Salesforce/codet5p-770m)
+--device                 Device to use: cuda, cpu, or mps (default: auto-detect)
+--n-perturbations        Number of perturbations per sample (default: 50)
+--batch-size             Batch size for processing (default: 10)
+--min-size               Minimum file size in bytes (default: 100)
+--max-size               Maximum file size in bytes (default: 100000)
+--max-files              Maximum files to process, 0 for all (default: 0)
+--device-info            Show device information and exit
+--debug                  Enable debug mode with full tracebacks
+```
+
+## How It Works
+
+DetectCodeGPT C++ Edition uses a multi-step detection process:
+
+1. **File Scanning**: Recursively scans directories for C++ files (.cpp, .hpp, .h, .cc, etc.)
+2. **Project Organization**: Groups files by project based on build system files (CMakeLists.txt, Makefile, etc.)
+3. **Code Preprocessing**: Normalizes and prepares C++ code for analysis
+4. **Perturbation Generation**: Creates multiple perturbed versions of each code sample
+5. **Likelihood Scoring**: Computes log-likelihood and rank scores using language models
+6. **Detection**: Applies DetectCodeGPT algorithm to classify code as AI-generated or human-written
+
+### Detection Scores
+
+The tool provides three main detection scores:
+
+- **DetectCodeGPT Score (NPR)**: Normalized Perturbation Rank - primary metric
+  - Values > 1.0: Likely AI-generated
+  - Values 0.95-1.0: Possibly AI-generated
+  - Values < 0.95: Likely human-written
+
+- **DetectGPT Score**: Curvature-based detection from original DetectGPT paper
+- **LRR Score**: Log-likelihood to Rank Ratio
+
+## Output Format
+
+### JSON Output
+
+The tool generates a comprehensive JSON file with:
+
+```json
+{
+  "metadata": {
+    "root_path": "/path/to/projects",
+    "timestamp": "2025-11-08T12:00:00",
+    "processing_time_seconds": 123.45,
+    "files_processed": 50,
+    "device_info": {...}
+  },
+  "summary": {
+    "total_analyzed": 50,
+    "likely_ai_generated": 5,
+    "possibly_ai_generated": 3,
+    "likely_human_written": 42,
+    "ai_percentage": 10.0
+  },
+  "projects": {
+    "project_name": [
+      {
+        "file_path": "/full/path/to/file.cpp",
+        "relative_path": "src/file.cpp",
+        "detection": {
+          "detectcodegpt_score": 1.05,
+          "prediction": "likely_ai_generated",
+          "confidence": "high",
+          ...
+        }
+      }
+    ]
+  }
+}
+```
+
+### Text Report
+
+Generate a human-readable summary:
+
+```
+================================================================================
+C++ AI-Generated Code Detection Report
+================================================================================
+
+Root Path: /path/to/projects
+Timestamp: 2025-11-08T12:00:00
+Processing Time: 123.45 seconds
+Device: cuda
+
+Summary:
+  Total Files Analyzed: 50
+  Likely AI-Generated: 5 (10.0%)
+  Possibly AI-Generated: 3
+  Likely Human-Written: 42
+  Errors: 0
+
+Projects:
+  project1:
+    Files: 25
+    Likely AI-Generated: 2
+    Suspicious files:
+      - src/algorithm.cpp (score: 1.0234)
+      - src/utils.cpp (score: 1.0156)
+```
+
+## Supported C++ File Types
+
+- `.cpp` - C++ source files
+- `.cc` - C++ source files (alternative extension)
+- `.cxx` - C++ source files (alternative extension)
+- `.c++` - C++ source files (alternative extension)
+- `.hpp` - C++ header files
+- `.h` - C/C++ header files
+- `.hh` - C++ header files (alternative extension)
+- `.hxx` - C++ header files (alternative extension)
+- `.h++` - C++ header files (alternative extension)
+
+## GPU Support
+
+The tool automatically detects and uses available GPUs:
+
+- **NVIDIA GPUs**: CUDA support (recommended)
+- **Apple Silicon**: Metal Performance Shaders (MPS)
+- **CPU Fallback**: Works without GPU but slower
+
+Check GPU availability:
+
+```bash
+python main_app.py --device-info
+```
+
+## Model Options
+
+### Base Models (for scoring)
+
+- `codellama/CodeLlama-7b-hf` (default, recommended for C++)
+- `codellama/CodeLlama-13b-hf` (larger, more accurate, slower)
+- `Salesforce/codegen-2B-mono`
+- `microsoft/CodeGPT-small-py`
+
+### Mask Filling Models
+
+- `Salesforce/codet5p-770m` (default, recommended)
+- `Salesforce/codet5-base`
+- `Salesforce/CodeT5-large`
+
+## Performance Tips
+
+1. **Use GPU**: Significant speedup with CUDA-capable GPU
+2. **Adjust Batch Size**: Increase for faster processing (if memory allows)
+3. **Reduce Perturbations**: Lower `n-perturbations` for faster but less accurate results
+4. **File Size Limits**: Adjust `min-size` and `max-size` to focus on relevant files
+5. **File Limit**: Use `max-files` for quick testing on large codebases
+
+## Troubleshooting
+
+### Out of Memory Errors
+
+- Reduce `batch-size`
+- Reduce `n-perturbations`
+- Use a smaller base model
+- Process fewer files at once with `max-files`
+
+### Slow Processing
+
+- Ensure GPU is being used (check with `--device-info`)
+- Increase `batch-size` if memory allows
+- Reduce `n-perturbations`
+
+### Import Errors
+
+Make sure all dependencies are installed:
+
+```bash
+pip install -r ../requirements.txt
+```
+
+## Examples
+
+### Scan a single project
+
+```bash
+python main_app.py --cli --directory ~/my_cpp_project --output results.json
+```
+
+### Scan with detailed reporting
+
+```bash
+python main_app.py --cli \
+    --directory ~/cpp_projects \
+    --output results.json \
+    --report detailed_report.txt \
+    --n-perturbations 100
+```
+
+### Quick scan for testing
+
+```bash
+python main_app.py --cli \
+    --directory ~/large_codebase \
+    --max-files 10 \
+    --n-perturbations 25
+```
+
+## License
+
+This project extends DetectCodeGPT and is licensed under the MIT License. See the LICENSE file in the repository root for details.
+
+## Citation
+
+If you use this tool in your research, please cite the original DetectCodeGPT paper:
+
+```bibtex
+@inproceedings{shi2025detectcodegpt,
+  title={Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmers},
+  author={Shi, Yuling and Zhang, Hongyu and Wan, Chengcheng and Gu, Xiaodong},
+  booktitle={Proceedings of the 47th International Conference on Software Engineering (ICSE 2025)},
+  year={2025},
+  organization={IEEE}
+}
+```
+
+## Acknowledgements
+
+Based on DetectCodeGPT by Shi et al., with enhancements for C++ code analysis, GPU acceleration, and user interface improvements.

cpp-detector/__init__.py

@@ -0,0 +1,19 @@
+"""
+DetectCodeGPT C++ Edition
+AI-generated C++ code detection with GPU acceleration and GUI.
+"""
+
+__version__ = "1.0.0"
+__author__ = "DetectCodeGPT Contributors"
+
+from .cpp_detector import CppCodeDetector, GPUManager
+from .file_scanner import CppFileScanner, scan_cpp_files
+from .batch_processor import BatchProcessor
+
+__all__ = [
+    'CppCodeDetector',
+    'GPUManager',
+    'CppFileScanner',
+    'scan_cpp_files',
+    'BatchProcessor'
+]