Mining Code Review Data to Understand Waiting Times Between Acceptance and Merging: An Empirical Analysis
Gunnar Kudrjavets (University of Groningen), Aditya Kumar (Snap,, Inc.), Nachiappan Nagappan (Meta Platforms, Inc.), Ayushi Rastogi (University, of Groningen)

TL;DR
This empirical study analyzes half a million code reviews to identify delays in the review process, highlighting opportunities to reduce waiting times and increase overall code velocity through automation and process improvements.
Contribution
The paper provides a detailed empirical analysis of review delays, quantifies potential speedups, and suggests automation as a way to reduce merging delays in code review workflows.
Findings
Reducing acceptance-to-merge time can speed up reviews by 29-63%.
Small changes and experienced authors have higher immediate acceptance rates.
Automatic merging can significantly increase code review velocity.
Abstract
Increasing code velocity (or the speed with which code changes are reviewed and merged) is integral to speeding up development and contributes to the work satisfaction of engineers. While factors affecting code change acceptance have been investigated in the past, solutions to decrease the code review lifetime are less understood. This study investigates the code review process to quantify delays and investigate opportunities to potentially increase code velocity. We study the temporal characteristics of half a million code reviews hosted on Gerrit and Phabricator, starting from the first response, to a decision to accept or reject the changes, and until the changes are merged into a target branch. We identified two types of time delays: (a) the wait time from the proposal of code changes until first response, and (b) the wait time between acceptance and merging. Our study indicates…
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Taxonomy
TopicsSoftware Engineering Research · Software System Performance and Reliability · Open Source Software Innovations
