The StatCodeSearch dataset is a benchmark test set consisting of code comment pairs extracted from R programming language scripts authored mostly by researchers. The dataset is sourced from the Open Science Framework (OSF). It includes text and code samples from R projects that pertain to the fields of social science and psychology with a focus on the statistical analysis of research data. As part of the GenCodeSearchNet test suite, this dataset can be used to test programming language understanding on a low resource programming language.
Semantic Code Search: using the comments as querries, return the matching code snippets from the set.
Code Classification: using the labels, classify the code snippets in to four categories: Data Variable, Visualization, Statistical Modeling, Statistical Test
BibTeX:
@inproceedings{diera2023gencodesearchnet,
title={GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding},
author={Diera, Andor and Dahou, Abdelhalim and Galke, Lukas and Karl, Fabian and Sihler, Florian and Scherp, Ansgar},
booktitle={Proceedings of the 1st GenBench Workshop on (Benchmarking) Generalisation in NLP},
pages={12--24},
year={2023}
}
5 commits
The StatCodeSearch dataset is a benchmark test set consisting of code comment pairs extracted from R programming language scripts authored mostly by researchers. The dataset is sourced from the Open Science Framework (OSF). It includes text and code samples from R projects that pertain to the fields of social science and psychology with a focus on the statistical analysis of research data. As part of the GenCodeSearchNet test suite, this dataset can be used to test programming language understanding on a low resource programming language.
Semantic Code Search: using the comments as querries, return the matching code snippets from the set.
Code Classification: using the labels, classify the code snippets in to four categories: Data Variable, Visualization, Statistical Modeling, Statistical Test
BibTeX:
@inproceedings{diera2023gencodesearchnet,
title={GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding},
author={Diera, Andor and Dahou, Abdelhalim and Galke, Lukas and Karl, Fabian and Sihler, Florian and Scherp, Ansgar},
booktitle={Proceedings of the 1st GenBench Workshop on (Benchmarking) Generalisation in NLP},
pages={12--24},
year={2023}
}
5 commits