Deciphering WONTFIX: A Mixed-Method Study on Why GitHub Issues Get Rejected

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Curtis, J. Alexander, Kasiviswanathan, Sharadha, Eisty, Nasir
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911188703510528
author Curtis, J. Alexander
Kasiviswanathan, Sharadha
Eisty, Nasir
author_facet Curtis, J. Alexander
Kasiviswanathan, Sharadha
Eisty, Nasir
contents Context: The ``wontfix'' label is a widely used yet narrowly understood tool in GitHub repositories, indicating that an issue will not be pursued further. Despite its prevalence, the impact of this label on project management and community dynamics within open-source software development is not clearly defined. Objective: This study examines the prevalence and reasons behind issues being labeled as wontfix across various open-source repositories on GitHub. Method: Employing a mixed-method approach, we analyze both quantitative data to assess the prevalence of the wontfix label and qualitative data to explore the reasoning that it was used. Data were collected from 3,132 of GitHub's most-popular repositories. Later, we employ open coding and thematic analysis to categorize the reasons behind wontfix labels, providing a structured understanding of the issue management landscape. Results: Our findings show that about 30% of projects on GitHub apply the wontfix label to some issues. These issues most often occur on user-submitted issues for bug reports and feature requests. The study identified eight common themes behind labeling issues as wontfix, ranging from user-specific control factors to maintainer-specific decisions. Conclusions: The wontfix label is a critical tool for managing resources and guiding contributor efforts in GitHub projects. However, it can also discourage community involvement and obscure the transparency of project management. Understanding these reasons aids project managers in making informed decisions and fostering efficient collaboration within open-source communities.
format Preprint
id arxiv_https___arxiv_org_abs_2510_01514
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Deciphering WONTFIX: A Mixed-Method Study on Why GitHub Issues Get Rejected
Curtis, J. Alexander
Kasiviswanathan, Sharadha
Eisty, Nasir
Software Engineering
Context: The ``wontfix'' label is a widely used yet narrowly understood tool in GitHub repositories, indicating that an issue will not be pursued further. Despite its prevalence, the impact of this label on project management and community dynamics within open-source software development is not clearly defined. Objective: This study examines the prevalence and reasons behind issues being labeled as wontfix across various open-source repositories on GitHub. Method: Employing a mixed-method approach, we analyze both quantitative data to assess the prevalence of the wontfix label and qualitative data to explore the reasoning that it was used. Data were collected from 3,132 of GitHub's most-popular repositories. Later, we employ open coding and thematic analysis to categorize the reasons behind wontfix labels, providing a structured understanding of the issue management landscape. Results: Our findings show that about 30% of projects on GitHub apply the wontfix label to some issues. These issues most often occur on user-submitted issues for bug reports and feature requests. The study identified eight common themes behind labeling issues as wontfix, ranging from user-specific control factors to maintainer-specific decisions. Conclusions: The wontfix label is a critical tool for managing resources and guiding contributor efforts in GitHub projects. However, it can also discourage community involvement and obscure the transparency of project management. Understanding these reasons aids project managers in making informed decisions and fostering efficient collaboration within open-source communities.
title Deciphering WONTFIX: A Mixed-Method Study on Why GitHub Issues Get Rejected
topic Software Engineering
url https://arxiv.org/abs/2510.01514