Expressions of Sentiments during Code Reviews: Male vs. Female

Abstract

Background: As most of the software development organizations are male-dominated, female developers encountering various negative workplace experiences reported feeling like they "do not belong". Exposures to discriminatory expletives or negative critiques from their male colleagues may further exacerbate those feelings.Aims: The primary goal of this study is to identify the differences in expressions of sentiments between male and female developers during various software engineering tasks.Method: On this goal, we mined the code review repositories of six popular open source projects. We used a semi-automated approach leveraging the name as well as multiple social networks to identify the gender of a developer. Using SentiSE, a customized and state-of-the-art sentiment analysis tool for the software engineering domain, we classify each communication as negative, positive, or neutral. We also compute the frequencies of sentiment words, emoticons, and expletives used by each developer.Results: Our results suggest that the likelihood of using sentiment words, emoticons, and expletives during code reviews varies based on the gender of a developer, as females are significantly less likely to express sentiments than males. Although female developers were more neutral to their male colleagues than to another female, male developers from three out of the six projects were not only writing more frequent negative comments but also withholding positive encouragements from their female counterparts.Conclusion: Our results provide empirical evidence of another factor behind the negative work place experiences encountered by the female developers that may be contributing to the diminishing number of females in the SE industry.

The SPACE of Developer Productivity

“…Research shows that women are more likely to receive negative comments and less likely to receive positive comments in their code reviews. 16 Any analysis of satisfaction with the review process should check for this in your environment. Understand that developers are likely influenced by the broader tech industry even if the patterns are not in your organization or team.…”

Social network analysis of open source software: A review and categorisation

“…Fine-Grain communication looks at how the contents of messages can be examined. Paul et al looked at sentiment expression differences between men and women in code reviews [50]. They found that women are less likely to display sentiment, and that men are more likely to express negative sentiment against women developers' submissions, and more likely to withhold positive comments.…”

Perceived diversity in software engineering: a systematic literature review

“…For example, findings show (1) significant gender differences in the features elected to use by developers and the willingness to tinker and explore features [SLR (Burnett et al 2010)], (2) men tend to switch more frequently between debugging strategies [SLR (Cao et al 2010)], (3) women tend toward underconfidence and men tend to use more unfamiliar software features [SLR ], (4) software environments are often aligned with the needs of men rather than women [SLR ; and (5) some end-user tools for debuggers may not fully support women debugging strategies [SLR (Subrahmaniyan et al 2008)]. Similarly, other studies report gender differences during code review practices indicate that (1) accepted pull requests submitted by women and men provide similar descriptions in terms of length, and generate a similar number of discussions [SLR (Imtiaz et al 2019)], (2) when both genders are known, women tend to have contributions accepted more often than men when they the contributors are from insiders to a project, but men's acceptance rates are higher when the contributors are from outsiders to a project, [SLR (Terrell et al 2017)], (3) while women concentrate their work across fewer projects and organizations, men contribute to a higher number of projects and organizations [SLR (Imtiaz et al 2019)], (4) there are gender differences in the use of positive opinion words, emoticons, and expletives during the code review as while men tend to express more positive/negative sentiments, women tend to express more neutral comments instead of expressing strong sentiments [SLR (Paul et al 2019)], and (5) men and women follow different comprehension strategies when reading source code [SLR (Zohreh Sharafi et al 2012)]. There are also gender differences in pair programming related to coordination, communication, and collaboration.…”