(previously BoDeGa)
An automated tool to identify bots in GitHub repositories by analysing pull request and issue comments. The tool has been developed by Mehdi Golzadeh, researcher at the Software Engineering Lab of the University of Mons (Belgium) as part of his PhD research in the context of the SECO-ASSIST Excellence of Science research project.
The tool accepts the name of a GitHub repository and requires a GitHub API key to compute its output in three steps. The first step consists of downloading all pull request comments and issue comments from the specified repository using the GitHub GraphQL API. This step results in a list of commenters and their corresponding pull request and issue comments. The second step consists of computing the following features that are needed for the classification model: the number of comments, empty comments, comment patterns, and inequality between the number of comments within patterns. The third step applies the classification model on the repository data and outputs the bot prediction made by the classification model.
Note about misclassifications The tool is based on a classification model that has been validated on a ground-truth dataset, and cannot reach a precision and recall of 100%. The accuracy may differ from one project to another, depending on the amount and types of accounts and comments. When running the tool on a GitHub repository of your choice, it is therefore possible that the tool may produce misclassifications in practice (humans misclassified as bots, or vice versa). For more details we refer to the association research publication. If you would encounter such situations while running the tool, please inform us about it, so that we can strive to further improve the accurracy of the classification algorithm. A known reason for the presence of misclassifations is the use of templates in pull request and issue comments by human commenters. Since the classification model's performance has been validated on accounts containing between 10 and 100 comments, the default parameters of the tool have been set to 10 for --min-comments and 100 for --max-comments. One can run the tool with other values on its own risk, without any guarantees on the accuracy.
This tool is a part of an empirical research endeavour aiming to identify bots in GitHub. A preprint of the research article, published in the Journal on Systems and Software, is available on arXiv. To cite this article, please use the following citation:
@article{Golzadeh2021JSS,
title={A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments},
author={Golzadeh, Mehdi and Decan, Alexandre and Legay, Damien and Mens, Tom},
year={2021},
volume = 175,
month = {may},
journal = {Journal of Systems and Software},
doi = {https://doi.org/10.1016/j.jss.2021.110911}
}
If you want to consult or cite the ground-truth dataset, please refer to the following citation:
@misc{Golzadeh2020dataset,
title={A ground-truth dataset to identify bots in GitHub},
author={Golzadeh, Mehdi and Decan, Alexandre and Legay, Damien and Mens, Tom},
year = 2020,
publisher = {Zenodo},
doi = {10.5281/zenodo.4000388},
URL = {http://doi.org/10.5281/zenodo.4000388}
}
To install BoDeGHa, run the following command:
pip install git+https://github.com/mehdigolzadeh/BoDeGHa
Given that this tool has many dependencies, and in order not to conflict with already installed packages, it is recommended to use a virtual environment before its installation. You can install and create a Python virtual environment and then install and run the tool in this environment. You can use any virtual environment of your choice. Below are the steps to install and create a virtual environment with virtualenv.
Use the following command to install the virtual environment:
pip install virtualenv
Create a virtual environment in the folder where you want to place your files:
virtualenv <name>
Start using the environment by:
source <name>/bin/activate
After running this command your command line prompt will change to (<name>) ... and now you can install BoDeGHa with the pip command.
When you are finished running the tool, you can quit the environment by:
deactivate
To run BoDeGHa you need to provide a GitHub personal access token (API key). You can follow the instructions here to obtain such a token (You don't need any of permissions in the list).
You can execute the tool with all default parameters by running bodegha repo_owner\repo_name --key <token>
Here is the list of parameters:
--accounts [ACCOUNT [ACCOUNT ...]] User login of one or more accounts
Example: $ bodegha repo_owner/repo_name --accounts mehdigolzadeh alexandredecan tommens --key
By default all accounts in the repository will be analysed
--start-date START_DATE Start date of pull request and issue comments in the repository to be considered
Example: $ bodegha repo_owner/repo_name --start-date 01-01-2018 --key
_The default start-date is 6 months before the current date.
--verbose To have verbose output result
Example: $ bodegha repo_owner/repo_name --verbose --key
The default value is false, if you don't pass this parameter the output will only be the accounts and their type
--min-comments MIN_COMMENTS Minimum number of pull request and issue comments that are required to analyze an account
Example: $ bodegha repo_owner/repo_name --min-comments 20 --key
The default value is 10 comments (the reason explained earlier in this file)
--max-comments MAX_COMMENTS Maximum number of pull request and issue comments to be considered for each account (default=100)
Example: $ bodegha repo_owner/repo_name --max-comments 120 --key
The default value is 100 comments (the reason explained earlier in this file)
--key APIKEY GitHub personal access token required to download comments from GitHub GraphQL API
This parameter is mandatory and you can obtain an access token as described earlier
--text Output results as plain text
--csv Output results in comma-separated values (csv) format
--json Output results in json format
Example: $ bodegha repo_owner/repo_name --json --key
This group of parameters is the type of output, e.g., if you pass --json you will get the result in JSON format
--exclude [ACCOUNT [ACCOUNT ...]] List of accounts to be excluded from the analysis
Example: $ bodegha repo_owner/repo_name --exclude mehdigolzadeh alexandredecan tommens --key
--only-predicted Only list accounts that the prediction is available
Example: $ bodegha repo_owner/repo_name --only-predicted
$ bodegha request/request --key <my token> --start-date 01-01-2017 --verbose --only-predicted
comments empty comments patterns dispersion prediction
account
greenkeeperio-bot 12 0 1 0.108246 Bot
stale 100 0 1 0.000000 Bot
FredKSchott 64 0 53 0.040618 Human
ahmadnassri 11 0 11 0.037776 Human
csvan 12 0 12 0.031019 Human
dvishniakov 11 0 9 0.068446 Human
hktalent 11 0 10 0.034367 Human
johnnysprinkles 12 0 11 0.033187 Human
mikeal 100 0 100 0.035073 Human
nicjansma 12 0 12 0.035834 Human
plroebuck 10 0 10 0.035052 Human
reconbot 93 0 81 0.036863 Human
simov 41 0 37 0.031932 Human
$ bodegha fthomas/refined --key <my token> --start-date 01-01-2017 --verbose --min-comments 20 --max-comments 90 --json --only-predicted
[{"account":"codecov","comments":90,"empty comments":0,"patterns":2,"dispersion":0.2501228703,"prediction":"Bot"},{"account":"codecov-io","comments":51,"empty comments":0,"patterns":2,"dispersion":0.2291022525,"prediction":"Bot"},{"account":"scala-steward","comments":90,"empty comments":0,"patterns":1,"dispersion":0.1819953352,"prediction":"Bot"},{"account":"NeQuissimus","comments":36,"empty comments":0,"patterns":36,"dispersion":0.0282932021,"prediction":"Human"},{"account":"erikerlandson","comments":20,"empty comments":1,"patterns":20,"dispersion":0.0314103784,"prediction":"Human"},{"account":"fthomas","comments":90,"empty comments":14,"patterns":63,"dispersion":0.0441094382,"prediction":"Human"},{"account":"howyp","comments":43,"empty comments":1,"patterns":43,"dispersion":0.0321397659,"prediction":"Human"}]
$ bodegha servo/servo --key <my token> --verbose --max-comments 80 --csv --accounts bors-servo Darkspirit Eijebong PeterZhizhin SimonSapin highfive --only-predicted
account,comments,empty comments,patterns,dispersion,prediction
bors-servo,80,0,11,0.12661359778212722,Bot
highfive,80,0,6,0.16390462912896814,Bot
Darkspirit,32,0,32,0.025969293313879968,Human
Eijebong,27,2,23,0.02551053114396642,Human
PeterZhizhin,13,0,12,0.025372037602093358,Human
SimonSapin,80,3,57,0.04771309733409579,Human
This tool is distributed under LGPLv3 - GNU Lesser General Public License, version 3.