metadata

license: mit
Programminglanguage: C
version: N/A
Date: '2015 POJ dataset from paper: https://arxiv.org/pdf/1409.5718.pdf'
Contaminated: Very Likely
Size: Standard Tokenizer

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-POJ-104 in Semeru

CodeXGLUE -- Clone Detection (POJ-104)

Task Definition

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.

Dataset

We use POJ-104 dataset on this task.

Data Format

For each file, each line in the uncompressed file represents one function. One row is illustrated below.

code: the source code
label: the number of problem that the source code solves
index: the index of example

Data Statistics

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

	#Problems	#Examples
Train	64	32,000
Dev	16	8,000
Test	24	12,000

Reference

@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}
}