Add dataset card

README.md

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+---
+dataset_info:
+  dataset_name: LineVul Dataset Splits
+  description: |
+    This dataset contains splits (train, validation, test) of the LineVul dataset, originally designed for transformer-based line-level vulnerability prediction in C/C++ code. It includes processed functions, vulnerability labels, and fixed versions of vulnerable functions.
+  version: 1.0.0
+  license: MIT
+  splits:
+    - name: train
+      description: Training split of the LineVul dataset.
+    - name: validation
+      description: Validation split of the LineVul dataset.
+    - name: test
+      description: Test split of the LineVul dataset.
+  features:
+    - name: processed_func
+      dtype: string
+      description: The original function written in C/C++.
+    - name: target
+      dtype: int
+      description: Function-level label (1 for vulnerable, 0 for non-vulnerable).
+    - name: vul_func_with_fix
+      dtype: string
+      description: The fixed function with added/deleted lines labeled.
+---
+
+# LineVul Dataset Splits
+
+This dataset provides the train, validation, and test splits of the LineVul dataset, originally introduced in the paper "LineVul: A Transformer-based Line-Level Vulnerability Prediction" by Michael Fu and Chakkrit Tantithamthavorn. The dataset is designed for predicting software vulnerabilities at the line level in C/C++ code using transformer-based models. It was sourced from the LineVul replication package available at [https://github.com/awsm-research/LineVul](https://github.com/awsm-research/LineVul).
+
+## Dataset Description
+
+The LineVul dataset consists of C/C++ functions with associated vulnerability labels and fixed versions. Each split (train, validation, test) contains 39 columns, but the key columns used for vulnerability prediction are:
+
+- **processed_func** (string): The original function written in C/C++.
+- **target** (int): A binary label indicating whether the function is vulnerable (1) or not (0).
+- **vul_func_with_fix** (string): The fixed version of the function, with added and deleted lines labeled.
+
+The dataset is intended for training and evaluating models that predict vulnerabilities in software code, particularly at the line level.
+
+## Citation
+
+The original dataset and methodology are detailed in the following paper:
+
+```bibtex
+@inproceedings{fu2022linevul,
+  title={LineVul: A Transformer-based Line-Level Vulnerability Prediction},
+  author={Fu, Michael and Tantithamthavorn, Chakkrit},
+  booktitle={2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR)},
+  year={2022},
+  organization={IEEE}
+}
+```
+
+Please cite this paper if you use this dataset in your research.
+
+## License
+
+The dataset is released under the [MIT License](https://opensource.org/licenses/MIT), consistent with the original LineVul replication package.
+
+