1. Engineering Impacts of Anonymous Author Code Review: A Field Experiment
- Author
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Ben Holtz, Lan Cheng, Ciera Jaspan, Emerson Murphy-Hill, Collin Green, Carolyn D. Egelman, Andrea Knight, Jillian Dicker, Elizabeth Kammer, Margaret Morrow Hodges, and Matthew Jorde
- Subjects
Focus (computing) ,Code review ,Computer science ,business.industry ,020207 software engineering ,02 engineering and technology ,computer.software_genre ,Data science ,Code (semiotics) ,Best coding practices ,Software ,0202 electrical engineering, electronic engineering, information engineering ,Identity (object-oriented programming) ,The Internet ,business ,computer - Abstract
Code review is a powerful technique to ensure high quality software and spread knowledge of best coding practices between engineers. Unfortunately, code reviewers may have biases about authors of the code they are reviewing, which can lead to inequitable experiences and outcomes. In principle, anonymous author code review can reduce the impact of such biases by withholding an author's identity from a reviewer. In this paper, to understand the engineering effects of using author anonymous code review in a practical setting, we applied the technique to 5217 code reviews performed by 300 software engineers at Google. Our results suggest that during anonymous author code review, reviewers can frequently guess authors identities; that focus is reduced on reviewer-author power dynamics; and that the practice poses a barrier to offline, high-bandwidth conversations. Based on our findings, we recommend that those who choose to implement anonymous author code review should reveal the time zone of the author by default, have a break-the-glass option for revealing author identity, and reveal author identity directly after the review.
- Published
- 2022