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license: mit
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license: mit
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### Dataset is imported from CodeXGLUE and pre-processed using their script.
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# Where to find in Semeru:
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The dataset can be found at /nfs/semeru/semeru_datasets/code_xglue/code-to-code/Clone-detection-POJ-104 in Semeru
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# CodeXGLUE -- Clone Detection (POJ-104)
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## Task Definition
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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@R score. MAP@R is defined as the mean of average precision scores, each of which is evaluated for retrieving R most similar samples given a query. For a code (query), R is the number of other codes in the same class, i.e. R=499 in this dataset.
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## Dataset
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We use [POJ-104](https://arxiv.org/pdf/1409.5718.pdf) dataset on this task.
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### Data Format
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For each file, each line in the uncompressed file represents one function. One row is illustrated below.
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- **code:** the source code
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- **label:** the number of problem that the source code solves
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- **index:** the index of example
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### Data Statistics
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Data statistics of the dataset are shown in the below table:
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| | #Problems | #Examples |
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| ----- | --------- | :-------: |
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| Train | 64 | 32,000 |
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| Dev | 16 | 8,000 |
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| Test | 24 | 12,000 |
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## Reference
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<pre><code>@inproceedings{mou2016convolutional,
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title={Convolutional neural networks over tree structures for programming language processing},
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author={Mou, Lili and Li, Ge and Zhang, Lu and Wang, Tao and Jin, Zhi},
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booktitle={Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence},
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pages={1287--1293},
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year={2016}
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}</code></pre>
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