Add dataset card

README.md

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+---
+# YAML Metadata Block
+language: 
+  - en
+tags:
+  - vulnerability-detection
+  - cve
+  - code-changes
+  - software-security
+  - stratified-split
+license: mit
+dataset_info:
+  features: # Features in the *final split files*
+    - name: idx
+      dtype: int64
+    - name: func_before
+      dtype: string
+    - name: Vulnerability Classification
+      dtype: string
+    - name: vul
+      dtype: int64
+    - name: func_after
+      dtype: string
+    - name: patch
+      dtype: string
+    - name: CWE ID
+      dtype: string
+    - name: lines_before
+      dtype: string
+    - name: lines_after
+      dtype: string
+  splits:
+    - name: train
+      num_examples: 150909
+    - name: validation
+      num_examples: 18864
+    - name: test
+      num_examples: 18863
+  
+ 
+  dataset_original_file_size: 10GB uuncompressed
+---
+
+# MSR Data Cleaned - C/C++ Code Vulnerability Dataset
+
+[![Dataset License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)
+
+
+
+## 📌 Dataset Description
+A curated collection of C/C++ code vulnerabilities paired with:
+- CVE details (scores, classifications, exploit status)
+- Code changes (commit messages, added/deleted lines)
+- File-level and function-level diffs
+
+## 🔍 Sample Data Structure from original file
+```python
++---------------+-----------------+----------------------+---------------------------+
+| CVE ID        | Attack Origin   | Publish Date         | Summary                   |
++===============+=================+======================+===========================+
+| CVE-2015-8467 | Remote          | 2015-12-29           | "The samldb_check_user..."|
++---------------+-----------------+----------------------+---------------------------+
+| CVE-2016-1234 | Local           | 2016-01-15           | "Buffer overflow in..."   |
++---------------+-----------------+----------------------+---------------------------+
+
+```
+Note: This is a simplified preview; the full dataset includes additional fields like commit_id, func_before, etc.
+
+
+### 1. Accessing in Colab
+```python
+!pip install huggingface_hub -q
+from huggingface_hub import snapshot_download
+
+repo_id = "starsofchance/MSR_data_cleaned"
+dataset_path = snapshot_download(repo_id=repo_id, repo_type="dataset")
+```
+
+### 2. Extracting the Dataset
+```python
+!apt-get install unzip -qq
+!unzip "/root/.cache/huggingface/.../MSR_data_cleaned.zip" -d "/content/extracted_data"
+```
+**Note: Extracted size is 10GB (1.5GB compressed). Ensure sufficient disk space.
+
+### 3. Creating Splits (Colab Pro Recommended)
+We used this memory-efficient approach:
+```python
+from datasets import load_dataset
+dataset = load_dataset("csv", data_files="MSR_data_cleaned.csv", streaming=True)
+
+# Randomly distribute rows (80-10-10)
+for row in dataset:
+    rand = random.random()
+    if rand < 0.8: write_to(train.csv)
+    elif rand < 0.9: write_to(validation.csv)
+    else: write_to(test.csv)
+```
+
+
+**Hardware Requirements:**
+- Minimum 25GB RAM
+- Strong CPU (Colab Pro T4 GPU recommended)
+
+##📊 Dataset Statistics
+
+- Number of Rows: 188,636
+- Vulnerability Distribution:
+	- Vulnerable (1): 18,863 (~10%)
+	- Non-Vulnerable (0): 169,773 (~90%)
+##📋 Data Fields Description
+- CVE_ID: Unique identifier for the vulnerability (Common Vulnerabilities and Exposures).
+- CWE_ID: Weakness category identifier (Common Weakness Enumeration).
+- Score: CVSS score indicating severity (float, 0-10).
+- Summary: Brief description of the vulnerability.
+- commit_id: Git commit hash linked to the code change.
+- codeLink: URL to the code repository or commit.
+- file_name: Name of the file containing the vulnerability.
+- func_after: Function code after the change.
+- lines_after: Code lines after the change.
+- Access_Gained: Type of access gained by exploiting the vulnerability.
+- Attack_Origin: Source of the attack (e.g., Remote, Local).
+- Authentication_Required: Whether authentication is needed to exploit.
+- Availability: Impact on system availability.
+- CVE_Page: URL to the CVE details page.
+- Complexity: Complexity of exploiting the vulnerability.
+- Confidentiality: Impact on data confidentiality.
+- Integrity: Impact on data integrity.
+- Known_Exploits: Details of known exploits, if any.
+- Publish_Date: Date the vulnerability was published.
+- Update_Date: Date of the last update to the vulnerability data.
+- Vulnerability_Classification: Type or category of the vulnerability.
+- add_lines: Lines added in the commit.
+- del_lines: Lines deleted in the commit.
+- commit_message: Description of the commit.
+- files_changed: List of files modified in the commit.
+- func_before: Function code before the change.
+- lang: Programming language (e.g., C, C++).
+- lines_before: Code lines before the change.
+
+
+## splits file for UltiVul project:
+
+## 🔍 Sample Data Structure (from train.csv)
+```python
+{
+ 'idx': 0, # Unique ID within the train split
+ 'func_before': '...', # String containing function code before change
+ 'Vulnerability Classification': '...', # Original vulnerability type classification
+ 'vul': 0, # Integer: 0 for non-vulnerable, 1 for vulnerable (target label)
+ 'func_after': '...', # String containing function code after change
+ 'patch': '...', # String containing diff patch
+ 'CWE ID': '...', # String CWE ID, e.g., "CWE-119"
+ 'lines_before': '...', # String lines before change context
+ 'lines_after': '...' # String lines after change context
+}
+```
+**Note: This shows the structure of the final split files (train.csv, validation.csv, test.csv). The original MSR_data_cleaned.csv contains many more metadata fields. 
+
+
+##📦 Dataset New Files
+The dataset is available as three CSV files (specially created for the UltiVul project) hosted on Hugging Face, uploaded via huggingface_hub:
+
+- train.csv
+	Size: 667 MB
+	Description: Training split with 150,909 samples, approximately 80% of the data.
+- validation.csv
+	Size: 86 MB
+	Description: Validation split with 18,864 samples, approximately 10% of the data.
+- test.csv
+	Size: 84.8 MB
+	Description: Test split with 18,863 samples, approximately 10% of the data.
+
+
+
+🙏 Acknowledgements
+Original dataset provided by Fan et al., 2020
+Thanks to the Hugging Face team for dataset hosting tools.
+
+## 📜 Citation
+```bibtex
+@inproceedings{fan2020ccode,
+  title={A C/C++ Code Vulnerability Dataset with Code Changes and CVE Summaries},
+  author={Fan, Jiahao and Li, Yi and Wang, Shaohua and Nguyen, Tien N},
+  booktitle={MSR '20: 17th International Conference on Mining Software Repositories},
+  pages={1--5},
+  year={2020},
+  doi={10.1145/3379597.3387501}
+}
+```
+
+## 🌟 Dataset Creation
+- **Source**: Original data from [MSR 2020 Paper](https://doi.org/10.1145/3379597.3387501)
+- **Processing**:
+  - Cleaned and standardized CSV format
+  - Stream-based splitting to handle large size
+  - Preserved all original metadata
+