Attend the Women in ML Symposium on December 7 Register now

code_x_glue_cc_defect_detection

参考:

使用以下命令在 TFDS 中加载此数据集:

ds = tfds.load('huggingface:code_x_glue_cc_defect_detection')
  • 说明
CodeXGLUE Defect-detection dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Defect-detection

Given a source code, the task is to identify whether it is an insecure code that may attack software systems, such as resource leaks, use-after-free vulnerabilities and DoS attack. We treat the task as binary classification (0/1), where 1 stands for insecure code and 0 for secure code.
The dataset we use comes from the paper Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks. We combine all projects and split 80%/10%/10% for training/dev/test.
  • 许可:无已知许可
  • 版本:0.0.0
  • 拆分
拆分 样本
'test' 2732
'train' 21854
'validation' 2732
  • 特征
{
    "id": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "func": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "target": {
        "dtype": "bool",
        "id": null,
        "_type": "Value"
    },
    "project": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "commit_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}