Pooja Rani
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---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- crowdsourced
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: 'Code-comment-classification
'
size_categories:
- 1K<n<10K
source_datasets:
- original
tags:
- '''source code comments'''
- '''java class comments'''
- '''python class comments'''
- '''
smalltalk class comments'''
task_categories:
- text-classification
task_ids:
- intent-classification
- multi-label-classification
---
# Dataset Card for Code Comment Classification
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:**https://github.com/poojaruhal/RP-class-comment-classification
- **Repository:**https://github.com/poojaruhal/RP-class-comment-classification
- **Paper: https:**//doi.org/10.1016/j.jss.2021.111047
- **Point of Contact:** Pooja Rani (https://poojaruhal.github.io)
### Dataset Summary
The dataset contains class comments extracted from various big and diverse open-source projects of three programming languages Java, Smalltalk, and Python.
### Supported Tasks and Leaderboards
Single-label text classification and Multi-label text classification
### Languages
Java, Python, Smalltalk
## Dataset Structure
### Data Instances
{
"class" : "Absy.java"
"comment":"* Azure Blob File System implementation of AbstractFileSystem. * This impl delegates to the old FileSystem"
"summary: "Azure Blob File System implementation of AbstractFileSystem."
"expand": "This impl delegates to the old FileSystem"
"rational":""
"deprecation":""
"usage":""
"exception":""
"todo":""
"incomplete":""
"commentedcode":""
"directive":""
"formatter":""
"license":""
"ownership":""
"pointer":""
"autogenerated":""
"noise":""
"warning":""
"recommendation":""
"precondition":""
"codingGuidelines":""
"extension":""
"subclassexplnation":""
"observation":""
}
### Data Fields
class: name of the class with the language extension
comment: class comment of the class
categories: a category that sentence is classified to. It indicated a particular type of information.
### Data Splits
10-fold cross validation
## Dataset Creation
### Curation Rationale
To identify the infomation embedded in the class comments across various projects and programming languages.
### Source Data
#### Initial Data Collection and Normalization
It contains the dataset extracted from various projects of three programming languages Java, Smalltalk, and Python.
- #### Java/
Contains all the extracted class comments of six java projects.
- [Eclipse.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/) - Extracted class comments from the Eclipse project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Eclipse](https://github.com/eclipse).
- [Guava.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/Guava.csv) - Extracted class comments from the Guava project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Guava](https://github.com/google/guava).
- [Guice.csv](/https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/Guice.csv) - Extracted class comments from the Guice project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Guice](https://github.com/google/guice).
- [Hadoop.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/Hadoop.csv) - Extracted class comments from the Hadoop project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Apache Hadoop](https://github.com/apache/hadoop)
- [Spark.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/Spark.csv) - Extracted class comments from the Apache Spark project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Apache Spark](https://github.com/apache/spark)
- [Vaadin.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/Vaadin.csv) - Extracted class comments from the Vaadin project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Vaadin](https://github.com/vaadin/framework)
- [Parser_Details.md](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Java/Parser_Details.md) - Details of the parser used to parse class comments of Java [ Projects](https://doi.org/10.5281/zenodo.4311839)
- #### Smalltalk/
Contains all the extracted class comments of seven Pharo projects.
- [GToolkit.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/GToolkit.csv) - Extracted class comments from the GToolkit project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [Moose.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/Moose.csv) - Extracted class comments from the Moose project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [PetitParser.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/PetitParser.csv) - Extracted class comments from the PetitParser project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [Pillar.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/Pillar.csv) - Extracted class comments from the Pillar project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [PolyMath.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/PolyMath.csv) - Extracted class comments from the PolyMath project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [Roassal2.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/Roassal2.csv) -Extracted class comments from the Roassal2 project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [Seaside.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/Seaside.csv) - Extracted class comments from the Seaside project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo.
- [Parser_Details.md](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Pharo/Parser_Details.md) - Details of the parser used to parse class comments of Pharo [ Projects](https://doi.org/10.5281/zenodo.4311839)
- #### Python/
Contains all the extracted class comments of seven Python projects.
- [Django.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Django.csv) - Extracted class comments from the Django project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Django](https://github.com/django)
- [IPython.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/IPython.csv) - Extracted class comments from the Ipython project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub[IPython](https://github.com/ipython/ipython)
- [Mailpile.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Mailpile.csv) - Extracted class comments from the Mailpile project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Mailpile](https://github.com/mailpile/Mailpile)
- [Pandas.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Pandas.csv) - Extracted class comments from the Pandas project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [pandas](https://github.com/pandas-dev/pandas)
- [Pipenv.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Pipenv.csv) - Extracted class comments from the Pipenv project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Pipenv](https://github.com/pypa/pipenv)
- [Pytorch.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Pytorch.csv) - Extracted class comments from the Pytorch project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [PyTorch](https://github.com/pytorch/pytorch)
- [Requests.csv](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Requests.csv) - Extracted class comments from the Requests project. The version of the project referred to extract class comments is available as [Raw Dataset](https://doi.org/10.5281/zenodo.4311839) on Zenodo. More detail about the project is available on GitHub [Requests](https://github.com/psf/requests/)
- [Parser_Details.md](https://github.com/poojaruhal/RP-class-comment-classification/tree/main/Dataset/RQ1/Python/Parser_Details.md) - Details of the parser used to parse class comments of Python [ Projects](https://doi.org/10.5281/zenodo.4311839)
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
Manual annoation. The details are given in the paper [Rani et al., JSS, 2021](https://doi.org/10.1016/j.jss.2021.111047)
#### Who are the annotators?
[Rani et al., JSS, 2021](https://doi.org/10.1016/j.jss.2021.111047)
### Personal and Sensitive Information
Author information embedded in the text
## Additional Information
### Dataset Curators
[Pooja Rani, Ivan, Manuel]
### Licensing Information
[license: cc-by-nc-sa-4.0]
### Citation Information
@article{RANI2021111047,
title = {How to identify class comment types? A multi-language approach for class comment classification},
journal = {Journal of Systems and Software},
volume = {181},
pages = {111047},
year = {2021},
issn = {0164-1212},
doi = {https://doi.org/10.1016/j.jss.2021.111047},
url = {https://www.sciencedirect.com/science/article/pii/S0164121221001448},
author = {Pooja Rani and Sebastiano Panichella and Manuel Leuenberger and Andrea {Di Sorbo} and Oscar Nierstrasz},
keywords = {Natural language processing technique, Code comment analysis, Software documentation}
}