docs/DATASET_CARD.md

# CodeReality-1T Dataset Card

## Dataset Summary

**CodeReality-1T** is a large-scale, deliberately noisy code repository dataset designed for robust AI research. The dataset contains **397,475 repositories** across **21 programming languages** in **3.05 TB** of uncompressed data, specifically curated to test robustness, data curation methods, and real-world code understanding.

- **Total Size**: 3.05 TB (uncompressed)
- **Repositories**: 397,475
- **Files**: 52,692 JSONL archives
- **Languages**: 21 detected languages
- **Status**: `deliberately_noisy: true` (research-only)
- **Version**: 1.0.0

## Dataset Structure

### Data Format
- **Format**: JSONL (JSON Lines) archives
- **Repository Structure**: Each line contains complete repository metadata including:
  - Source code files with full paths
  - Git commit history and messages
  - Issue tracking data
  - Repository metadata (stars, forks, topics)
  - License information (when available)

### Language Distribution
Based on complete analysis of all 397,475 repositories:

| Language | Repositories | Percentage |
|----------|-------------|------------|
| Unknown | 389,941 | 98.1% |
| Python | 4,738 | 1.2% |
| Shell | 4,505 | 1.1% |
| C | 3,969 | 1.0% |
| C++ | 3,339 | 0.8% |
| HTML | 2,487 | 0.6% |
| JavaScript | 2,394 | 0.6% |
| Go | 2,110 | 0.5% |
| Java | 2,026 | 0.5% |
| Others | 1,966 | 0.5% |

### Domain Distribution
Cross-domain analysis reveals:

| Domain | Repositories | Cross-Domain |
|--------|-------------|--------------|
| General | 389,941 | - |
| Database | 7,534 | ✓ |
| AI/ML | 7,534 | ✓ |
| Systems | 7,534 | ✓ |
| Security | 7,534 | ✓ |
| Web | 7,429 | ✓ |
| Enterprise | 7,072 | ✓ |
| Gaming | 6,538 | ✓ |
| Mobile | 5,705 | ✓ |
| Scientific | 5,386 | ✓ |
| DevOps | 4,600 | ✓ |

**Cross-domain repositories**: 59,332 (14.9%)

## Motivation

Real-world code repositories are inherently messy, containing:
- Duplicate code and forked repositories
- Incomplete or experimental code snippets
- Mixed licensing conditions
- Buggy commits and partial implementations
- DevOps configurations and non-code artifacts

CodeReality-1T embraces this complexity as a **research laboratory** for:

1. **Robustness Testing**: How do code LLMs perform on noisy, real-world data?
2. **Data Curation Methods**: Developing better filtering and cleaning techniques
3. **License Compliance**: Research into automated license detection and filtering
4. **Bug-Fix Alignment**: Studying commit patterns for before/after code analysis
5. **NL↔Code Tasks**: Natural language to code alignment through issues, commits, and documentation

## Collection Process

### Sources
- Public GitHub repositories
- GitLab public projects
- Open source package registries
- Developer forum code dumps

### Acquisition Pipeline
1. **Repository Harvesting**: Systematic collection from public sources
2. **Metadata Extraction**: Complete git history, issues, documentation
3. **Format Standardization**: Conversion to JSONL with consistent schema
4. **Indexing**: SHA256 checksums and comprehensive cataloging

### Filtering Strategy
**Deliberately Minimal Filtering** to preserve research value:
- ✅ **Kept**: Forks, duplicates, incomplete code, experimental projects
- ✅ **Kept**: Repositories with unknown or missing licenses
- ✅ **Kept**: Multi-language and cross-domain projects
- ❌ **Excluded**: Only explicitly "all rights reserved" repositories

### Quality Assurance
- **100% Coverage**: Complete analysis without sampling
- **Integrity Verification**: SHA256 checksums for all files
- **Comprehensive Indexing**: Full metadata extraction and validation
- **Reproducible Pipeline**: Open source tools only (enry, scancode-toolkit, PyDriller)

## Technical Characteristics

### File Type Distribution (Top 15)
| Extension | Files | Description |
|-----------|-------|-------------|
| .h | 34,195,463 | C/C++ headers |
| .go | 18,691,961 | Go source |
| .java | 18,109,114 | Java source |
| .c | 16,700,728 | C source |
| .py | 15,650,558 | Python source |
| .ts | 10,271,948 | TypeScript |
| .cpp | 9,768,211 | C++ source |
| .md | 7,815,310 | Markdown docs |
| .rs | 7,280,129 | Rust source |
| .rb | 6,309,814 | Ruby source |
| .json | 5,888,235 | JSON data |
| .txt | 4,627,011 | Text files |
| .rst | 4,250,204 | reStructuredText |
| .js | 4,125,928 | JavaScript |
| .scala | 3,619,096 | Scala source |

### Build Systems Detected
| Build System | Occurrences | Ecosystem |
|--------------|-------------|-----------|
| Makefile | 619,857 | C/C++/Universal |
| package.json | 510,769 | Node.js/npm |
| build.gradle | 430,334 | Java/Android |
| pom.xml | 136,386 | Java/Maven |
| requirements.txt | 57,793 | Python/pip |

### Development Patterns Analysis
Based on **49,140 commit messages** analyzed:

| Pattern | Count | Percentage |
|---------|-------|------------|
| Bug fixes | 21,570 | 43.9% |
| New features | 11,580 | 23.6% |
| Testing | 6,483 | 13.2% |
| Documentation | 4,695 | 9.6% |
| Improvements | 4,477 | 9.1% |
| Refactoring | 335 | 0.7% |

## Uses

### Primary Research Applications
1. **Code LLM Robustness**: Testing model performance on noisy, real-world data
2. **Data Curation Research**: Developing automated filtering and cleaning methods
3. **License Detection**: Training and evaluating license classification systems
4. **Bug-Fix Studies**: Before/after commit analysis for automated debugging
5. **Cross-Language Analysis**: Multi-language repository understanding
6. **DevOps Research**: Configuration file analysis and validation

### Specific Task Examples
- **Deduplication**: Identify and remove duplicate code across repositories
- **License Classification**: Automated SPDX license detection and compliance
- **Issue→Code Retrieval**: Generate code solutions from natural language descriptions
- **Commit Message Generation**: Automatic commit message creation from code diffs
- **Build System Analysis**: Configuration file validation and optimization
- **Security Scanning**: Identifying potential vulnerabilities and secrets

## Limitations

### License Coverage
- **0% License Detection Rate**: All repositories marked as "Unknown" in current release
- **Manual Review Required**: Commercial use requires individual license verification
- **Research Use Recommended**: Dataset optimized for academic and research applications

### Data Quality Issues
- **98.1% Unknown Language**: Large portion of repositories with undetected language
- **Deliberately Noisy**: Intentionally includes incomplete, experimental, and duplicate code
- **Exact Duplicates**: 0% exact SHA256 duplicates detected across file-level content
- **Semantic Duplicates**: ~18% estimated semantic duplicates and forks preserved by design (includes repository forks, copy-pasted code, and similar implementations)
- **Intentional Design**: Duplicates are preserved to study real-world code distribution and test deduplication algorithms
- **Security Concerns**: Contains potential API keys, passwords, and tokens (see Security Analysis)

### Representation Bias
- **Language Skew**: Heavy bias toward C/C++, Python, JavaScript ecosystems
- **Geographic Bias**: Primarily English-language repositories and comments
- **Temporal Bias**: Snapshot from specific time period, may not reflect current practices

### Scale Limitations
- **Processing Requirements**: 3.05 TB requires significant storage and computational resources
- **Filtering Needed**: Most use cases will require substantial preprocessing
- **Network Intensive**: Large download size may limit accessibility

## Security Analysis

### Detected Security Patterns
Comprehensive security scan revealed:

| Pattern Type | Occurrences | Risk Level |
|--------------|-------------|------------|
| Password patterns | 1,231,942 | High |
| Token patterns | 353,266 | High |
| Secret patterns | 71,778 | Medium |
| API key patterns | 4,899 | Critical |

### Security Recommendations
⚠️ **WARNING**: This dataset contains potential secrets and should be used for research only
- **No Production Use**: Never deploy code from this dataset without thorough security review
- **Credential Scanning**: Always scan extracted code for hardcoded credentials
- **Isolation Required**: Use in sandboxed environments only
- **Legal Compliance**: Verify licensing before any commercial application

## Ethical Considerations

### Privacy & Consent
- **Public Data Only**: All repositories were publicly available at collection time
- **No Private Information**: No deliberately collected private repositories or data
- **Takedown Policy**: DMCA and removal requests will be honored promptly

### Bias & Fairness
- **Representation Issues**: Dataset reflects existing biases in open source development
- **Language Barriers**: Primarily English-language codebases and documentation
- **Economic Bias**: Overrepresents well-resourced development environments

### Legal Compliance
- **License Uncertainty**: Many repositories lack clear licensing information
- **Commercial Risk**: Use in commercial products requires individual license verification
- **Attribution**: Original repository attribution preserved in metadata

## Evaluation Framework

### Evaluation Subset (Available)
A curated evaluation subset is now available:
- **Size**: 19.0 GB (323 files, 2,049 repositories)
- **Selection Criteria**:
  - Research value scoring with diversity sampling
  - Repositories with enhanced metadata and commit history
  - Cross-language implementations and multi-repo files
  - Complete build system configurations
- **Location**: `/eval/subset/` with comprehensive metadata

### Baseline Tasks & Results
1. **Code Completion**: Pass@k evaluation → [Results: 14.2% Pass@1](../eval/results/code_completion_sample_results.json)
2. **License Classification**: Automated detection → [Results: 9.8% accuracy](../eval/results/license_detection_sample_results.json)
3. **Bug Detection**: Commit history analysis → [Framework available](../eval/benchmarks/bug_detection_benchmark.py)
4. **Cross-Language Translation**: Code equivalence → [Framework available](../eval/benchmarks/cross_language_translation_benchmark.py)
5. **Complete Analysis**: [Summary CSV](../eval/results/benchmark_summary.csv) for research comparison

### Metrics
- **Functional Correctness**: Pass@k, CodeBLEU, execution success rate
- **Information Retrieval**: MRR, MAP, BLEU scores for search and generation
- **Classification Accuracy**: Precision, recall, F1 for license and bug detection

## Distribution

### Access Information

**📦 Full Dataset (3.05 TB)**:
- **Status**: Hosting in progress on Hugging Face Hub
- **Content**: Complete 397,475 repositories, 52,692 JSONL files
- **Distribution**: `codereality/codereality-1t` (pending)
- **Alternatives**: Torrent and S3 bucket options planned

**📋 Evaluation Subset (19.0 GB)**:
- **Status**: Available now
- **Content**: 2,049 curated repositories, 323 JSONL files
- **Location**: `/eval/subset/` directory
- **Purpose**: Research benchmarks and evaluation tasks

**📚 Documentation & Tools**:
- **GitHub Repository**: Complete analysis scripts and benchmarks
- **Benchmark Results**: Sample baselines and comparison data

### File Organization
```
codereality-1t/
├── data/
│   ├── *.jsonl              # Repository archives (52,692 files)
│   └── manifest.json        # File checksums and metadata
├── analysis/
│   ├── dataset_index.json   # Complete file index
│   ├── metrics.json         # Analysis results
│   └── language_stats.json  # Language distribution
├── docs/
│   ├── DATASET_CARD.md      # This document
│   ├── LICENSE.md           # Dataset license
│   └── USAGE_EXAMPLES.md    # Code examples
└── eval/
    ├── subset/              # Evaluation subset (15.1GB, available)
    └── benchmarks/          # Evaluation scripts
```

### Checksums & Integrity
- **Hash Algorithm**: SHA256
- **Manifest File**: Complete checksums for all 52,692 JSONL files
- **Verification**: `sha256sum -c manifest.json`

## Maintenance & Support

### Contact Information
- **Primary Maintainer**: Vincenzo Gallo (vincenzo.gallo77@hotmail.com)
- **Issue Tracker**: https://github.com/vinsguru/codereality-1t/issues
- **Repository**: https://github.com/vinsguru/codereality-1t

### Update Policy
- **Version 1.0.0**: Initial deliberately noisy release
- **Future Versions**: May include cleaned/curated variants
- **Community Contributions**: Cleaning scripts, evaluation tasks, and analysis tools welcome

### Contribution Guidelines
1. **Bug Reports**: Use GitHub issues for data quality problems
2. **Enhancement Requests**: Suggest improvements via pull requests
3. **Research Papers**: Share research using this dataset for community benefit
4. **Derived Datasets**: Coordinate to avoid duplication and ensure proper attribution

## Version History

### v1.0.0 (Current)
- **Release Date**: September 2025
- **Content**: Complete 3.05 TB deliberately noisy dataset
- **Analysis**: Full BigCode-compliant metrics on all 397,475 repositories
- **Status**: Research-ready with comprehensive documentation

### Community-Driven Roadmap
CodeReality-1T is a **living dataset** that evolves with community contributions:

- **v1.1.0 (Q1 2025)**: Enhanced evaluation subset with community feedback, improved benchmarks, and additional task frameworks
- **v1.2.0 (Q2 2025)**: License detection improvements, deduplication analysis tools, semantic duplicate estimation, and community filtering scripts
- **v2.0.0 (Q3 2025)**: Community-curated clean variant with quality filters, improved metadata, and production-ready subset

**Community contributions actively encouraged**: cleaning scripts, new benchmarks, evaluation tasks, data curation improvements, and quality assessment tools.

## Citation

```bibtex
@misc{codereality2025,
  title={CodeReality-1T: A Large-Scale Deliberately Noisy Dataset for Robust Code Understanding},
  author={Vincenzo Gallo},
  year={2025},
  publisher={Hugging Face},
  howpublished={\\url{https://huggingface.co/vinsblack}},
  note={Version 1.0.0}
}
```

## License

This dataset is released under [License Terms] with the following considerations:
- **Research Use**: Freely available for academic and research purposes
- **Commercial Use**: Requires individual license verification for each repository
- **Attribution**: Please cite this dataset card and preserve original repository attribution
- **Liability**: Provided as-is with no warranties regarding licensing or content accuracy

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*Dataset Card generated automatically from comprehensive analysis of all 397,475 repositories using BigCode-compliant methodology. Analysis completed in 63.7 hours with 100% coverage and no sampling.*