A Longitudinal Analysis of Good First Issue Practices and Newcomer Pull Requests in Popular OSS Projects

2026-04-30

AI Summary

This study investigates the temporal evolution of the effectiveness of the "Good First Issue" (GFI) mechanism in open-source projects. Through a longitudinal analysis of over 400,000 issues and 1,117 new contributors’ GFI-related pull requests across 37 popular GitHub repositories over four years, it reveals a significant decline in the availability of GFI-labeled issues since 2024. While the rate of new contributor participation has remained stable at approximately 27%, the merge rate of their pull requests has dropped markedly from 61.9% to 42.2%, indicating a weakening efficacy of the GFI mechanism. Furthermore, the study finds that characteristics of initial pull requests fail to predict their eventual merge outcomes, challenging prevailing assumptions and highlighting a growing disconnect between current GFI practices and the retention of new contributors.

Abstract

Open-source software (OSS) projects rely on effective newcomer onboarding to sustain their communities. OSS projects widely adopt "good first issue" (GFI) labels to highlight beginner-friendly tasks. As development practices continue to evolve, understanding how these onboarding mechanisms change over time is important for both maintainers and researchers. This study analyzes 406,826 issues and 1,117 newcomer GFI pull requests across 37 popular GitHub repositories (30 of which use GFI labels) over a four-year period from July 2021 to June 2025. We find that while the proportion of issues with GFI labels remained stable during the first three years, it underwent a statistically significant decline beginning in January 2024, with substantial variation across projects not explained by repository age or programming language. Despite this supply-side decline, newcomer engagement with GFI issues remains stable at approximately 27%, suggesting that GFI labels maintain consistent attractiveness. Examining the outcomes of this engagement, we find that the merge rate of newcomer GFI pull requests declined from 61.9% to 42.2%. Initial pull request characteristics such as description length and code size show no significant association with merge outcomes, indicating that success is not predicted by the quantitative characteristics of the initial submission alone. Together, these findings reveal a widening gap between stable newcomer interest in GFIs and the declining availability and success of GFI-based onboarding, underscoring the need for maintainers to sustain both GFI labeling and review support.

Problem

• Good First Issue
• Newcomer Onboarding
• Open-Source Software
• Pull Request Merge Rate
• Longitudinal Analysis

Innovation

• Good First Issue
• Newcomer Onboarding
• Longitudinal Analysis
• Pull Request Merge Rate
• Open-Source Software