---
license: cc-by-4.0
task_categories:
- text-retrieval
- text-classification
language:
- code
size_categories:
- 1K<n<10K
pretty_name: statcodesearch
---
# Dataset Card for statcodesearch

<!-- Provide a quick summary of the dataset. -->

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.

## Dataset Details


### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** https://github.com/drndr/gencodesearchnet
- **Paper [optional]:** https://arxiv.org/abs/2311.09707
  
## Uses

- **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


## Dataset Structure

- **Id**: unique identifier for each item
- **Comment**: full string of a comment describing a code snippet
- **Code**: full string of a code snippet
- **Label**: class of a code snippet
- **Source**: the OSF repository of the extracted code-comment pair
- **File**: the name of the R file of the extracted code-comment pair from the OSF repository


## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**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}
}
```