Datasets:
Tasks:
Text Classification
Formats:
parquet
Sub-tasks:
semantic-similarity-classification
Languages:
code
Size:
1M - 10M
License:
Commit
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02fcf85
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Parent(s):
46c2a16
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{"default": {"description": "CodeXGLUE Clone-detection-BigCloneBench dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Clone-detection-BigCloneBench\n\nGiven two codes as the input, the task is to do binary classification (0/1), where 1 stands for semantic equivalence and 0 for others. Models are evaluated by F1 score.\nThe dataset we use is BigCloneBench and filtered following the paper Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree.", "citation": "@inproceedings{svajlenko2014towards,\ntitle={Towards a big data curated benchmark of inter-project code clones},\nauthor={Svajlenko, Jeffrey and Islam, Judith F and Keivanloo, Iman and Roy, Chanchal K and Mia, Mohammad Mamun},\nbooktitle={2014 IEEE International Conference on Software Maintenance and Evolution},\npages={476--480},\nyear={2014},\norganization={IEEE}\n}\n\n@inproceedings{wang2020detecting,\ntitle={Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree},\nauthor={Wang, Wenhan and Li, Ge and Ma, Bo and Xia, Xin and Jin, Zhi},\nbooktitle={2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)},\npages={261--271},\nyear={2020},\norganization={IEEE}\n}", "homepage": "https://github.com/madlag/CodeXGLUE/tree/main/Code-Code/Clone-detection-BigCloneBench", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "id1": {"dtype": "int32", "id": null, "_type": "Value"}, "id2": {"dtype": "int32", "id": null, "_type": "Value"}, "func1": {"dtype": "string", "id": null, "_type": "Value"}, "func2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "bool", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "label", "output": ""}, "task_templates": null, "builder_name": "code_x_glue_cc_clone_detection_big_clone_bench", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2888035757, "num_examples": 901028, "dataset_name": "code_x_glue_cc_clone_detection_big_clone_bench"}, "validation": {"name": "validation", "num_bytes": 1371399694, "num_examples": 415416, "dataset_name": "code_x_glue_cc_clone_detection_big_clone_bench"}, "test": {"name": "test", "num_bytes": 1220662901, "num_examples": 415416, "dataset_name": "code_x_glue_cc_clone_detection_big_clone_bench"}}, "download_checksums": {"https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/Clone-detection-BigCloneBench/dataset/train.txt": {"num_bytes": 17043552, "checksum": "29119bfa94673374249c3424809fbe6baaa1f0e87a13e3c727bbd6cdf1224b77"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/Clone-detection-BigCloneBench/dataset/data.jsonl": {"num_bytes": 15174797, "checksum": "d8bc51e62deddcc45bd26c5b57f5add2a2cf377f13b9f6c2fb656fbc8fca4dd2"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/Clone-detection-BigCloneBench/dataset/valid.txt": {"num_bytes": 7861019, "checksum": "e59e8c1321df59b6ab0143165cb603030c55800c00e2d782e06810517b8de1e4"}, "https://raw.githubusercontent.com/madlag/CodeXGLUE/main/Code-Code/Clone-detection-BigCloneBench/dataset/test.txt": {"num_bytes": 7876506, "checksum": "a6c0cf79be34e582fdc64007aa894ed094e4f9ff2e5395a8d2b5c39eeef2737a"}}, "download_size": 47955874, "post_processing_size": null, "dataset_size": 5480098352, "size_in_bytes": 5528054226}}
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