
### Dataset is imported from CodeXGLUE and pre-processed using their script.

# Where to find in Semeru:
The dataset can be found at /nfs/semeru/semeru_datasets/code_xglue/code-to-code/Clone-detection-BigCloneBench in Semeru


# CodeXGLUE -- Clone Detection (BCB)

## Task Definition

Given 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.

## Updates

2021-9-13: We have update the evaluater script. Since it's a binary classification, we use binary F1 score instead of "macro" F1 score.

## Dataset

The dataset we use is [BigCloneBench](https://www.cs.usask.ca/faculty/croy/papers/2014/SvajlenkoICSME2014BigERA.pdf) and filtered following the paper [Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree](https://arxiv.org/pdf/2002.08653.pdf).

### Data Format

1. dataset/data.jsonl is stored in jsonlines format. Each line in the uncompressed file represents one function.  One row is illustrated below.

   - **func:** the function

   - **idx:** index of the example

2. train.txt/valid.txt/test.txt provide examples, stored in the following format:    idx1	idx2	label

### Data Statistics

Data statistics of the dataset are shown in the below table:

|       | #Examples |
| ----- | :-------: |
| Train |  901,028  |
| Dev   |  415,416  |
| Test  |  415,416  |





## Reference
<pre><code>@inproceedings{svajlenko2014towards,
  title={Towards a big data curated benchmark of inter-project code clones},
  author={Svajlenko, Jeffrey and Islam, Judith F and Keivanloo, Iman and Roy, Chanchal K and Mia, Mohammad Mamun},
  booktitle={2014 IEEE International Conference on Software Maintenance and Evolution},
  pages={476--480},
  year={2014},
  organization={IEEE}
}

@inproceedings{wang2020detecting,
  title={Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree},
  author={Wang, Wenhan and Li, Ge and Ma, Bo and Xia, Xin and Jin, Zhi},
  booktitle={2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)},
  pages={261--271},
  year={2020},
  organization={IEEE}
}</code></pre>

license:mit arxiv:2002.08653 region:us
{"license": "mit", "Programminglanguage": "Java", "version": "N/A", "Date": "2014 Big clone bench paper https://www.cs.usask.ca/faculty/croy/papers/2014/SvajlenkoICSME2014BigERA.pdf", "Contaminated": "Very Likely", "Size": "Standard Tokenizer"}
TAGS
#license-mit #arxiv-2002.08653 #region-us 

### Dataset is imported from CodeXGLUE and pre-processed using their script.


Where to find in Semeru:
========================


The dataset can be found at /nfs/semeru/semeru\_datasets/code\_xglue/code-to-code/Clone-detection-BigCloneBench in Semeru


CodeXGLUE -- Clone Detection (BCB)
==================================


Task Definition
---------------


Given 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.


Updates
-------


2021-9-13: We have update the evaluater script. Since it's a binary classification, we use binary F1 score instead of "macro" F1 score.


Dataset
-------


The dataset we use is BigCloneBench and filtered following the paper Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree.


### Data Format


1. dataset/URL is stored in jsonlines format. Each line in the uncompressed file represents one function. One row is illustrated below.


	* func: the function
	* idx: index of the example
2. URL provide examples, stored in the following format: idx1 idx2 label


### Data Statistics


Data statistics of the dataset are shown in the below table:



Reference
---------



```
@inproceedings{svajlenko2014towards,
  title={Towards a big data curated benchmark of inter-project code clones},
  author={Svajlenko, Jeffrey and Islam, Judith F and Keivanloo, Iman and Roy, Chanchal K and Mia, Mohammad Mamun},
  booktitle={2014 IEEE International Conference on Software Maintenance and Evolution},
  pages={476--480},
  year={2014},
  organization={IEEE}
}

@inproceedings{wang2020detecting,
  title={Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree},
  author={Wang, Wenhan and Li, Ge and Ma, Bo and Xia, Xin and Jin, Zhi},
  booktitle={2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)},
  pages={261--271},
  year={2020},
  organization={IEEE}
}
```


### Dataset is imported from CodeXGLUE and pre-processed using their script.


Where to find in Semeru:
========================


The dataset can be found at /nfs/semeru/semeru\_datasets/code\_xglue/code-to-code/Clone-detection-BigCloneBench in Semeru


CodeXGLUE -- Clone Detection (BCB)
==================================


Task Definition
---------------


Given 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.


Updates
-------


2021-9-13: We have update the evaluater script. Since it's a binary classification, we use binary F1 score instead of "macro" F1 score.


Dataset
-------


The dataset we use is BigCloneBench and filtered following the paper Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree. ### Data Format


1. dataset/URL is stored in jsonlines format. Each line in the uncompressed file represents one function. One row is illustrated below.


	* func: the function
	* idx: index of the example
2. URL provide examples, stored in the following format: idx1 idx2 label ### Data Statistics


Data statistics of the dataset are shown in the below table:



Reference
---------



```
@inproceedings{svajlenko2014towards,
  title={Towards a big data curated benchmark of inter-project code clones},
  author={Svajlenko, Jeffrey and Islam, Judith F and Keivanloo, Iman and Roy, Chanchal K and Mia, Mohammad Mamun},
  booktitle={2014 IEEE International Conference on Software Maintenance and Evolution},
  pages={476--480},
  year={2014},
  organization={IEEE}
}

@inproceedings{wang2020detecting,
  title={Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree},
  author={Wang, Wenhan and Li, Ge and Ma, Bo and Xia, Xin and Jin, Zhi},
  booktitle={2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)},
  pages={261--271},
  year={2020},
  organization={IEEE}
}
```
TAGS
#license-mit #arxiv-2002.08653 #region-us 
 ### Dataset is imported from CodeXGLUE and pre-processed using their script.


Where to find in Semeru:
========================


The dataset can be found at /nfs/semeru/semeru\_datasets/code\_xglue/code-to-code/Clone-detection-BigCloneBench in Semeru


CodeXGLUE -- Clone Detection (BCB)
==================================


Task Definition
---------------


Given 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.


Updates
-------


2021-9-13: We have update the evaluater script. Since it's a binary classification, we use binary F1 score instead of "macro" F1 score.


Dataset
-------


The dataset we use is BigCloneBench and filtered following the paper Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree. ### Data Format


1. dataset/URL is stored in jsonlines format. Each line in the uncompressed file represents one function. One row is illustrated below.


	* func: the function
	* idx: index of the example
2. URL provide examples, stored in the following format: idx1 idx2 label ### Data Statistics


Data statistics of the dataset are shown in the below table:



Reference
---------



```
@inproceedings{svajlenko2014towards,
  title={Towards a big data curated benchmark of inter-project code clones},
  author={Svajlenko, Jeffrey and Islam, Judith F and Keivanloo, Iman and Roy, Chanchal K and Mia, Mohammad Mamun},
  booktitle={2014 IEEE International Conference on Software Maintenance and Evolution},
  pages={476--480},
  year={2014},
  organization={IEEE}
}

@inproceedings{wang2020detecting,
  title={Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree},
  author={Wang, Wenhan and Li, Ge and Ma, Bo and Xia, Xin and Jin, Zhi},
  booktitle={2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)},
  pages={261--271},
  year={2020},
  organization={IEEE}
}
```
passage: TAGS
#license-mit #arxiv-2002.08653 #region-us 
### Dataset is imported from CodeXGLUE and pre-processed using their script.


Where to find in Semeru:
========================


The dataset can be found at /nfs/semeru/semeru\_datasets/code\_xglue/code-to-code/Clone-detection-BigCloneBench in Semeru


CodeXGLUE -- Clone Detection (BCB)
==================================


Task Definition
---------------


Given 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.


Updates
-------


2021-9-13: We have update the evaluater script. Since it's a binary classification, we use binary F1 score instead of "macro" F1 score.


Dataset
-------


The dataset we use is BigCloneBench and filtered following the paper Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree.### Data Format


1. dataset/URL is stored in jsonlines format. Each line in the uncompressed file represents one function. One row is illustrated below.


	* func: the function
	* idx: index of the example
2. URL provide examples, stored in the following format: idx1 idx2 label