Dataset:

Task Categories: text-retrieval
Languages: code
Multilinguality: monolingual
Size Categories: 10K<n<100K
Licenses: other-C-UDA
Language Creators: found
Annotations Creators: found
Source Datasets: original

Dataset Card for "code_x_glue_cc_clone_detection_poj_104"

Dataset Summary

CodeXGLUE Clone-detection-POJ-104 dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/Clone-detection-POJ-104

Given a code and a collection of candidates as the input, the task is to return Top K codes with the same semantic. Models are evaluated by MAP score. We use POJ-104 dataset on this task.

Supported Tasks and Leaderboards

  • document-retrieval: The dataset can be used to train a model for retrieving top-k codes with the same semantics.

Languages

  • C++ programming language

Dataset Structure

Data Instances

An example of 'train' looks as follows.

{
    "code": "\nint f(int shu,int min)\n{ \n  int k=1;\n  if(shu < min)\n  { \n    k= 0; \n   return k;\n  } \n  else\n {\n  for(int i = min;i<shu;i++)\n  { \n    if(shu%i == 0)\n    { \n         k=k+ f(shu/i,i); \n    } \n  \n    \n  } \n    return k; \n}\n} \n\nmain()\n{\n      int n,i,a;\n      scanf(\"%d\",&n);\n      \n      for(i=0;i<n;i++)\n      {\n          scanf(\"%d\",&a);\n          \n          if(i!=n-1)                                                        \n           printf(\"%d\\n\",f(a,2));\n           else\n           printf(\"%d\",f(a,2));                           \n                                      \n                     \n                      \n      }              \n                     \n                      \n                      }", 
    "id": 0, 
    "label": "home"
}

Data Fields

In the following each data field in go is explained for each config. The data fields are the same among all splits.

default

field name type description
id int32 Index of the sample
code string The full text of the function
label string The id of problem that the source code solves

Data Splits

name train validation test
default 32000 8000 12000

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

https://github.com/microsoft, https://github.com/madlag

Licensing Information

Computational Use of Data Agreement (C-UDA) License.

Citation Information

@inproceedings{mou2016convolutional,
  title={Convolutional neural networks over tree structures for programming language processing},
  author={Mou, Lili and Li, Ge and Zhang, Lu and Wang, Tao and Jin, Zhi},
  booktitle={Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence},
  pages={1287--1293},
  year={2016}
}

Contributions

Thanks to @madlag (and partly also @ncoop57) for adding this dataset.

Models trained or fine-tuned on code_x_glue_cc_clone_detection_poj104

None yet