SEAug 17, 2021

Are Code Review Processes Influenced by the Genders of the Participants?

arXiv:2108.07774v2Has Code
Originality Synthesis-oriented
AI Analysis

It addresses diversity issues in software development by examining potential gender-based disparities, but it is an incremental replication of prior studies.

This study investigates whether gender biases affect code review outcomes and participation in Free and open-source software communities, focusing on code acceptance, review intervals, and participation rates.

Background: Contemporary software development organizations lack diversity and the ratios of women in Free and open-source software (FOSS) communities are even lower than the industry average. Although the results of recent studies hint the existence of biases against women, it is unclear to what extent such biases influence the outcomes of software development tasks. Objective: This study aims to conceptually replicate two recent studies investigating gender biases in FOSS communities \textit{ to identify whether the outcomes of or participation in code reviews (or pull requests) are influenced by the gender of a developer.} In particular, this study focuses on two outcome aspects (i.e., code acceptance, and review interval) and one participation aspect (i.e., code review participation) of code review processes. Method: We will augment the dataset used in the original studies with code reviews /pull requests created during recent years. Using this dataset, we will train multivariate regression models to accurately model the influences of developers' genders on code acceptance, review intervals, and code review participation.

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