# The Impact of Human Factors on the Participation Decision of Reviewers in Modern Code Review

arXiv: https://arxiv.org/abs/1806.10277 · HTML: https://mlsanity.com/paper/1806.10277/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jun 2018.

## Built on by (most cited first, 5 of 5)

- [Using Machine Intelligence to Prioritise Code Review Requests](https://mlsanity.com/paper/2102.05916/) (2021)
- [Rethinking Code Review in the Age of AI: A Vision for Agentic Code Review](https://mlsanity.com/paper/2605.17548/) (2026)
- [Predicting Code Review Completion Time in Modern Code Review](https://mlsanity.com/paper/2109.15141/) (2021)
- [Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?](https://mlsanity.com/paper/2110.05035/) (2021)
- [Practitioners' Challenges and Perceptions of CI Build Failure Predictions at Atlassian](https://mlsanity.com/paper/2402.09651/) (2024)

## Abstract (arXiv)

Modern Code Review (MCR) plays a key role in software quality practices. In MCR process, a new patch (i.e., a set of code changes) is encouraged to be examined by reviewers in order to identify weaknesses in source code prior to an integration into main software repositories. To mitigate the risk of having future defects, prior work suggests that MCR should be performed with sufficient review participation. Indeed, recent work shows that a low number of participated reviewers is associated with poor software quality. However, there is a likely case that a new patch still suffers from poor review participation even though reviewers were invited. Hence, in this paper, we set out to investigate the factors that are associated with the participation decision of an invited reviewer. Through a case study of 230,090 patches spread across the Android, LibreOffice, OpenStack and Qt systems, we find that (1) 16%-66% of patches have at least one invited reviewer who did not respond to the review invitation; (2) human factors play an important role in predicting whether or not an invited reviewer will participate in a review; (3) a review participation rate of an invited reviewers and code authoring experience of an invited reviewer are highly associated with the participation decision of an invited reviewer. These results can help practitioners better understand about how human factors associate with the participation decision of reviewers and serve as guidelines for inviting reviewers, leading to a better inviting decision and a better reviewer participation.