Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study

Fuente: arXiv
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Auteurs principaux: Stray, Viktoria, Brandtzæg, Elias Goldmann, Wivestad, Viggo Tellefsen, Barbala, Astri, Moe, Nils Brede
Format: Preprint
Publié: 2025
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author Stray, Viktoria
Brandtzæg, Elias Goldmann
Wivestad, Viggo Tellefsen
Barbala, Astri
Moe, Nils Brede
author_facet Stray, Viktoria
Brandtzæg, Elias Goldmann
Wivestad, Viggo Tellefsen
Barbala, Astri
Moe, Nils Brede
contents This study investigates the real-world impact of the generative AI (GenAI) tool GitHub Copilot on developer activity and perceived productivity. We conducted a mixed-methods case study in NAV IT, a large public sector agile organization. We analyzed 26,317 unique non-merge commits from 703 of NAV IT's GitHub repositories over a two-year period, focusing on commit-based activity metrics from 25 Copilot users and 14 non-users. The analysis was complemented by survey responses on their roles and perceived productivity, as well as 13 interviews. Our analysis of activity metrics revealed that individuals who used Copilot were consistently more active than non-users, even prior to Copilot's introduction. We did not find any statistically significant changes in commit-based activity for Copilot users after they adopted the tool, although minor increases were observed. This suggests a discrepancy between changes in commit-based metrics and the subjective experience of productivity.
format Preprint
id arxiv_https___arxiv_org_abs_2509_20353
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study
Stray, Viktoria
Brandtzæg, Elias Goldmann
Wivestad, Viggo Tellefsen
Barbala, Astri
Moe, Nils Brede
Software Engineering
This study investigates the real-world impact of the generative AI (GenAI) tool GitHub Copilot on developer activity and perceived productivity. We conducted a mixed-methods case study in NAV IT, a large public sector agile organization. We analyzed 26,317 unique non-merge commits from 703 of NAV IT's GitHub repositories over a two-year period, focusing on commit-based activity metrics from 25 Copilot users and 14 non-users. The analysis was complemented by survey responses on their roles and perceived productivity, as well as 13 interviews. Our analysis of activity metrics revealed that individuals who used Copilot were consistently more active than non-users, even prior to Copilot's introduction. We did not find any statistically significant changes in commit-based activity for Copilot users after they adopted the tool, although minor increases were observed. This suggests a discrepancy between changes in commit-based metrics and the subjective experience of productivity.
title Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study
topic Software Engineering
url https://arxiv.org/abs/2509.20353