Update README.md

README.md

@@ -1,37 +1,44 @@
 ---
-dataset_name: "CodeReality"
-pretty_name: "CodeReality: Deliberately Noisy Code Dataset"
+dataset_name: "CodeReality-EvalSubset"
+pretty_name: "CodeReality: Evaluation Subset - Deliberately Noisy Code Dataset"
 tags:
-- code
-- bigcode
-- software-engineering
-- robustness
-- noisy-dataset
-- evaluation
+  - code
+  - software-engineering
+  - robustness
+  - noisy-dataset
+  - evaluation-subset
+  - research-dataset
+  - code-understanding
 size_categories:
-- 10GB<n<100GB
-- 1TB<n<10TB
+  - 10GB<n<100GB
 task_categories:
-- text-generation
-- text-classification
-- text-retrieval
-- other
+  - text-generation
+  - text-classification
+  - text-retrieval
+  - code-completion
+  - license-detection
+  - cross-language-analysis
 language:
-- en
+  - en
+  - code
 license: other
 configs:
-- config_name: default
-  data_files:
-  - eval/subset/*.jsonl
+  - config_name: default
+    data_files:
+      - "data/*.jsonl"
+  - config_name: benchmarks
+    data_files:
+      - "benchmarks/*.py"
+      - "results/*.json"
 ---
 
 
-
-# CodeReality: Large-Scale Deliberately Noisy Code Dataset
+# CodeReality: Evaluation Subset - Deliberately Noisy Code Dataset
 
 ![Dataset Status](https://img.shields.io/badge/status-complete-brightgreen)
-![Size](https://img.shields.io/badge/size-3.05TB-orange)
-![Repositories](https://img.shields.io/badge/repositories-397,475-red)
+![Size](https://img.shields.io/badge/size-19GB-orange)
+![Repositories](https://img.shields.io/badge/repositories-2,049-red)
+![Subset](https://img.shields.io/badge/type-evaluation_subset-purple)
 
 ## ⚠️ Important Limitations
 
@@ -41,11 +48,11 @@ configs:
 
 ## Overview
 
-**CodeReality-1T** is a large-scale, deliberately noisy code repository dataset designed for robust AI research. 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.
+**CodeReality Evaluation Subset** is a curated research subset extracted from the complete CodeReality dataset (3.05TB, 397,475 repositories). This subset contains **2,049 repositories** in **19GB** of data, specifically selected for standardized evaluation and benchmarking of code understanding models on deliberately noisy data.
 
 ### Key Features
-- ✅ **Complete Coverage**: 100% analysis of all 397,475 repositories (no sampling)
-- ✅ **BigCode Compliant**: Meets all community standards for transparency and reproducibility
+- ✅ **Curated Selection**: Research value scoring with diversity sampling from 397,475 repositories
+- ✅ **Research Grade**: Comprehensive analysis with transparent methodology
 - ✅ **Deliberately Noisy**: Includes duplicates, incomplete code, and experimental projects
 - ✅ **Rich Metadata**: Enhanced Blueprint metadata with cross-domain classification
 - ✅ **Professional Grade**: 63.7-hour comprehensive analysis with open source tools
@@ -55,17 +62,22 @@ configs:
 ### Dataset Structure
 ```
 codereality-1t/
-├── data/                    # Main dataset location reference
+├── data/                    # Evaluation subset data (19GB, 323 JSONL files)
 │   ├── README.md           # Data access instructions
-│   └── manifest.json      # Integrity verification
-├── analysis/               # Analysis results
-│   ├── dataset_index.json  # Complete file index (29MB)
-│   └── metrics.json        # Comprehensive analysis results
+│   └── [323 JSONL files]  # Repository data in JSON Lines format
+├── analysis/               # Analysis results and tools
+│   ├── dataset_index.json  # File index and metadata
+│   └── metrics.json        # Analysis results
 ├── docs/                   # Documentation
 │   ├── DATASET_CARD.md     # Comprehensive dataset card
 │   └── LICENSE.md          # Licensing information
-└── eval/                   # Evaluation subset (in progress)
-    └── subset/             # Curated 15GB research subset
+├── benchmarks/             # Benchmarking scripts and frameworks
+├── results/                # Evaluation results and metrics
+├── Notebook/               # Analysis notebooks and visualizations
+├── eval_metadata.json      # Evaluation metadata and statistics
+├── dataset-config.yaml     # Main dataset configuration
+├── analysis-config.yaml    # Analysis methodology and results configuration
+└── benchmarks-config.yaml  # Benchmarking framework configuration
 ```
 
 ### Loading the Dataset
@@ -74,17 +86,19 @@ codereality-1t/
 import json
 import os
 
-# Load dataset index
-with open('analysis/dataset_index.json', 'r') as f:
-    index = json.load(f)
+# Load evaluation subset metadata
+with open('eval_metadata.json', 'r') as f:
+    metadata = json.load(f)
 
-print(f"Files: {len(index['files'])}")
-print(f"Repositories: {sum(f['repository_count'] for f in index['files'])}")
+print(f"Subset: {metadata['eval_subset_info']['name']}")
+print(f"Files: {metadata['subset_statistics']['total_files']}")
+print(f"Repositories: {metadata['subset_statistics']['estimated_repositories']}")
+print(f"Size: {metadata['subset_statistics']['total_size_gb']} GB")
 
-# Access data files
-data_dir = "/mnt/z/CodeReality_Final/unified_dataset"
-for file_info in index['files'][:5]:  # First 5 files
-    file_path = file_info['path']
+# Access evaluation data files
+data_dir = "data/"  # Local evaluation subset data
+for filename in os.listdir(data_dir)[:5]:  # First 5 files
+    file_path = os.path.join(data_dir, filename)
     with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
         for line in f:
             repo_data = json.loads(line)
@@ -94,12 +108,13 @@ for file_info in index['files'][:5]:  # First 5 files
 
 ## Dataset Statistics
 
-### Scale
-- **Total Repositories**: 397,475
-- **Total Files**: 52,692 JSONL archives
-- **Total Size**: 3.05 TB uncompressed
-- **Languages Detected**: 21
-- **Analysis Coverage**: 100% (no sampling)
+### Evaluation Subset Scale
+- **Total Repositories**: 2,049 (curated from 397,475)
+- **Total Files**: 323 JSONL archives
+- **Total Size**: 19GB uncompressed
+- **Languages Detected**: Multiple (JavaScript, Python, Java, C/C++, mixed)
+- **Selection**: Research value scoring with diversity sampling
+- **Source Dataset**: CodeReality complete dataset (3.05TB)
 
 ### Language Distribution (Top 10)
 | Language | Repositories | Percentage |
@@ -141,14 +156,16 @@ for file_info in index['files'][:5]:  # First 5 files
 4. **Bug-Fix Studies**: Before/after commit analysis for automated debugging
 5. **Cross-Language Analysis**: Multi-language repository understanding
 
-### Evaluation Subset & Benchmarks
-A curated **19GB evaluation subset** is now available for standardized benchmarks:
+### About This Evaluation Subset
+This repository contains the **19GB evaluation subset** designed for standardized benchmarks:
 - **323 files** containing **2,049 repositories**
 - Research value scoring with diversity sampling
 - Cross-language implementations and multi-repo analysis
 - Complete build system configurations
 - Enhanced metadata with commit history and issue tracking
 
+**Note**: The complete 3.05TB CodeReality dataset with all 397,475 repositories is available separately. Contact vincenzo.gallo77@hotmail.com for access to the full dataset.
+
 **Demonstration Benchmarks** available in `eval/benchmarks/`:
 - **License Detection**: Automated license classification evaluation
 - **Code Completion**: Pass@k metrics for code generation models
@@ -191,6 +208,91 @@ python3 code_completion_benchmark.py      # Code generation Pass@k
 - **Security Risk**: Contains potential secrets and vulnerabilities
 - **Deliberately Noisy**: Requires preprocessing for most applications
 
+## ⚠️ Important: Dataset vs Evaluation Subset
+
+**This repository contains the 19GB evaluation subset only.** Some files within this repository (such as `docs/DATASET_CARD.md`, notebooks in `Notebook/`, and analysis results) reference or describe the complete 3.05TB CodeReality dataset. This is intentional for research context and documentation completeness.
+
+### What's in this repository:
+- ✅ **Evaluation subset data**: 19GB, 2,049 repositories in `data/` directory
+- ✅ **Analysis tools and scripts**: For working with both subset and full dataset
+- ✅ **Documentation**: Describes both the subset and the complete dataset methodology
+- ✅ **Benchmarks**: Ready to use with the evaluation subset
+
+### Complete Dataset Access (3.05TB):
+- 📧 **Contact**: vincenzo.gallo77@hotmail.com for access to the full dataset
+- 📊 **Full Scale**: 397,475 repositories across 21 programming languages
+- 🗂️ **Size**: 3.05TB uncompressed, 52,692 JSONL files
+
+#### Who Should Use the Complete Dataset:
+- 🎯 **Large-scale ML researchers** training foundation models on massive code corpora
+- 🏢 **Enterprise teams** developing production code understanding systems
+- 🔬 **Academic institutions** conducting comprehensive code analysis studies
+- 📊 **Data scientists** performing statistical analysis on repository distributions
+- 🛠️ **Tool developers** building large-scale code curation and filtering systems
+
+#### Advantages of Complete Dataset vs Evaluation Subset:
+| Feature | Evaluation Subset (19GB) | Complete Dataset (3.05TB) |
+|---------|-------------------------|---------------------------|
+| **Repositories** | 2,049 curated | 397,475 complete coverage |
+| **Use Case** | Benchmarking & evaluation | Large-scale training & research |
+| **Data Quality** | High (curated selection) | Mixed (deliberately noisy) |
+| **Languages** | Multi-language focused | 21+ languages comprehensive |
+| **Setup Time** | Immediate | Requires infrastructure planning |
+| **Best For** | Model evaluation, testing | Model training, comprehensive analysis |
+
+#### Choose Complete Dataset When:
+- ✅ Training large language models requiring massive code corpora
+- ✅ Developing data curation algorithms at scale
+- ✅ Studying real-world code distribution patterns
+- ✅ Building production-grade code understanding systems
+- ✅ Researching cross-language programming patterns
+- ✅ Creating comprehensive code quality metrics
+
+#### Choose Evaluation Subset When:
+- ✅ Benchmarking existing models
+- ✅ Quick prototyping and testing
+- ✅ Learning to work with noisy code datasets
+- ✅ Limited storage or computational resources
+- ✅ Focused evaluation on curated, high-value repositories
+
+## Configuration Files (YAML)
+
+The project includes comprehensive YAML configuration files for easy programmatic access:
+
+| Configuration File | Description |
+|-------------------|-------------|
+| [`dataset-config.yaml`](dataset-config.yaml) | Main dataset metadata and structure |
+| [`analysis-config.yaml`](analysis-config.yaml) | Analysis methodology and results |
+| [`benchmarks-config.yaml`](benchmarks-config.yaml) | Benchmarking framework configuration |
+
+### Using Configuration Files
+
+```python
+import yaml
+
+# Load dataset configuration
+with open('dataset-config.yaml', 'r') as f:
+    dataset_config = yaml.safe_load(f)
+
+print(f"Dataset: {dataset_config['dataset']['name']}")
+print(f"Version: {dataset_config['dataset']['version']}")
+print(f"Total repositories: {dataset_config['dataset']['metadata']['total_repositories']}")
+
+# Load analysis configuration
+with open('analysis-config.yaml', 'r') as f:
+    analysis_config = yaml.safe_load(f)
+
+print(f"Analysis time: {analysis_config['analysis']['methodology']['total_time_hours']} hours")
+print(f"Coverage: {analysis_config['analysis']['methodology']['coverage_percentage']}%")
+
+# Load benchmarks configuration
+with open('benchmarks-config.yaml', 'r') as f:
+    benchmarks_config = yaml.safe_load(f)
+
+for benchmark in benchmarks_config['benchmarks']['available_benchmarks']:
+    print(f"Benchmark: {benchmark}")
+```
+
 ## Documentation
 
 | Document | Description |
@@ -203,30 +305,30 @@ python3 code_completion_benchmark.py      # Code generation Pass@k
 
 Verify dataset integrity:
 ```bash
-# Check file counts
+# Check evaluation subset counts
 python3 -c "
 import json
-with open('analysis/dataset_index.json', 'r') as f:
-    idx = json.load(f)
-    print(f'Files: {len(idx[\"files\"])}')
-    print(f'Repositories: {sum(f[\"repository_count\"] for f in idx[\"files\"])}')
+with open('eval_metadata.json', 'r') as f:
+    metadata = json.load(f)
+    print(f'Files: {metadata[\"subset_statistics\"][\"total_files\"]}')
+    print(f'Repositories: {metadata[\"subset_statistics\"][\"estimated_repositories\"]}')
+    print(f'Size: {metadata[\"subset_statistics\"][\"total_size_gb\"]} GB')
 "
 
 # Expected output:
-# Files: 52692
-# Repositories: 397475
+# Files: 323
+# Repositories: 2049
+# Size: 19.0 GB
 ```
 
 ## Citation
 
 ```bibtex
 @misc{codereality2025,
-  title={CodeReality-1T: A Large-Scale Deliberately Noisy Dataset for Robust Code Understanding},
+  title={CodeReality Evaluation Subset: A Curated Research Dataset for Robust Code Understanding},
   author={Vincenzo Gallo},
   year={2025},
-  publisher={Hugging Face},
-  howpublished={\\url{https://huggingface.co/vinsblack}},
-  note={Version 1.0.0}
+  note={Version 1.0.0 - Evaluation Subset (19GB from 3.05TB source)}
 }
 ```
 
@@ -259,17 +361,38 @@ We welcome community contributions to improve CodeReality-1T:
 - **Documentation**: Usage examples, tutorials, case studies
 
 **📋 Contribution Process**:
-1. Check Issues for current needs and coordination2
-2. Create feature branch for your contribution
-3. Submit pull request with detailed description and testing
-4. Engage in community review and discussions
+1. Clone the repository locally
+2. Review existing analysis in the `analysis/` directory
+3. Develop improvements or new features
+4. Test your contributions thoroughly
+5. Submit your improvements via standard collaboration methods
+
+**💡 Join the Community**: Share your research, tools, and insights using CodeReality!
+
+## Support & Access
+
+### Evaluation Subset (This Repository)
+- **Documentation**: See `docs/` directory for comprehensive information
+- **Analysis**: Check `analysis/` directory for current research insights
+- **Usage**: All benchmarks and tools work directly with the 19GB subset
+
+### Complete Dataset Access (3.05TB)
+- **🔗 Full Dataset Request**: Contact vincenzo.gallo77@hotmail.com
+- **📋 Include in your request**:
+  - Research purpose and intended use
+  - Institutional affiliation (if applicable)
+  - Technical requirements and storage capacity
+- **⚡ Response time**: Typically within 24-48 hours
+
+### General Support
+- **Technical Questions**: vincenzo.gallo77@hotmail.com
+- **Documentation Issues**: Check `docs/` directory first
+- **Benchmark Problems**: Review `benchmarks/` and `results/` directories
 
-**💡 Join the Community**: Share your research, tools, and insights using CodeReality-1T!
+---
+
+*Dataset created using transparent research methodology with complete reproducibility. Analysis completed in 63.7 hours with 100% coverage and no sampling.*
 
-## Support
 
-- **Documentation**: See `docs/` directory
-- **Contact**: vincenzo.gallo77@hotmail.com
 
----