Datasets:
Tasks:
Translation
Modalities:
Text
Formats:
parquet
Size:
100K - 1M
ArXiv:
Tags:
text-to-code
License:
| annotations_creators: | |
| - found | |
| language_creators: | |
| - found | |
| language: | |
| - code | |
| - en | |
| license: | |
| - c-uda | |
| multilinguality: | |
| - other-programming-languages | |
| size_categories: | |
| - 100K<n<1M | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - translation | |
| task_ids: [] | |
| pretty_name: CodeXGlueTcTextToCode | |
| tags: | |
| - text-to-code | |
| # Dataset Card for "code_x_glue_tc_text_to_code" | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits-sample-size) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** https://github.com/microsoft/CodeXGLUE/tree/main/Text-Code/text-to-code | |
| ### Dataset Summary | |
| CodeXGLUE text-to-code dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Code/text-to-code | |
| The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/. | |
| ### Supported Tasks and Leaderboards | |
| - `machine-translation`: The dataset can be used to train a model for generating Java code from an **English** natural language description. | |
| ### Languages | |
| - Java **programming** language | |
| ## Dataset Structure | |
| ### Data Instances | |
| An example of 'train' looks as follows. | |
| ``` | |
| { | |
| "code": "boolean function ( ) { return isParsed ; }", | |
| "id": 0, | |
| "nl": "check if details are parsed . concode_field_sep Container parent concode_elem_sep boolean isParsed concode_elem_sep long offset concode_elem_sep long contentStartPosition concode_elem_sep ByteBuffer deadBytes concode_elem_sep boolean isRead concode_elem_sep long memMapSize concode_elem_sep Logger LOG concode_elem_sep byte[] userType concode_elem_sep String type concode_elem_sep ByteBuffer content concode_elem_sep FileChannel fileChannel concode_field_sep Container getParent concode_elem_sep byte[] getUserType concode_elem_sep void readContent concode_elem_sep long getOffset concode_elem_sep long getContentSize concode_elem_sep void getContent concode_elem_sep void setDeadBytes concode_elem_sep void parse concode_elem_sep void getHeader concode_elem_sep long getSize concode_elem_sep void parseDetails concode_elem_sep String getType concode_elem_sep void _parseDetails concode_elem_sep String getPath concode_elem_sep boolean verify concode_elem_sep void setParent concode_elem_sep void getBox concode_elem_sep boolean isSmallBox" | |
| } | |
| ``` | |
| ### Data Fields | |
| In the following each data field in go is explained for each config. The data fields are the same among all splits. | |
| #### default | |
| |field name| type | description | | |
| |----------|------|---------------------------------------------| | |
| |id |int32 | Index of the sample | | |
| |nl |string| The natural language description of the task| | |
| |code |string| The programming source code for the task | | |
| ### Data Splits | |
| | name |train |validation|test| | |
| |-------|-----:|---------:|---:| | |
| |default|100000| 2000|2000| | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| [More Information Needed] | |
| ### Personal and Sensitive Information | |
| [More Information Needed] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| https://github.com/microsoft, https://github.com/madlag | |
| ### Licensing Information | |
| Computational Use of Data Agreement (C-UDA) License. | |
| ### Citation Information | |
| ``` | |
| @article{iyer2018mapping, | |
| title={Mapping language to code in programmatic context}, | |
| author={Iyer, Srinivasan and Konstas, Ioannis and Cheung, Alvin and Zettlemoyer, Luke}, | |
| journal={arXiv preprint arXiv:1808.09588}, | |
| year={2018} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to @madlag (and partly also @ncoop57) for adding this dataset. |