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Thu 12 Nov 2020 01:35 - 01:36 at Virtual room 1 - Community

Code review is a critical step in modern software quality assurance, yet it is vulnerable to human biases.
Previous studies have clarified the extent of the problem, particularly regarding biases against the authors of code,but no consensus understanding has emerged.
Advances in medical imaging are increasingly applied to software engineering, supporting grounded neurobiological explorations of computing activities, including the review, reading, and writing of source code.
In this paper, we present the results of a controlled experiment using both medical imaging and also eye tracking to investigate the neurological correlates of biases and differences between genders of humans and machines (e.g., automated program repair tools) in code review.
We find that men and women conduct code reviews differently, in ways that are measurable and supported by behavioral, eye-tracking and medical imaging data.
We also find biases in how humans review code as a function of its apparent author, when controlling for code quality.
In addition to advancing our fundamental understanding of how cognitive biases relate to the code review process, the results may inform subsequent training and tool design to reduce bias.

Conference Day
Thu 12 Nov

Displayed time zone: (UTC) Coordinated Universal Time change

01:30 - 02:00
01:30
2m
Talk
A First Look at Good First Issues on GitHub
Research Papers
Xin TanPeking University, China, Minghui ZhouPeking University, China, Zeyu SunPeking University, China
DOI
01:32
2m
Talk
A Theory of the Engagement in Open Source Projects via Summer of Code Programs
Research Papers
Jefferson SilvaPUC-SP, Brazil, Igor WieseFederal University of Technology ParanĂ¡, Brazil, Daniel M. GermanUniversity of Victoria, Canada, Christoph TreudeUniversity of Adelaide, Australia, Marco GerosaNorthern Arizona University, USA, Igor SteinmacherNorthern Arizona University, USA
DOI
01:35
1m
Talk
Biases and Differences in Code Review using Medical Imaging and Eye-Tracking: Genders, Humans, and Machines
Research Papers
Yu HuangUniversity of Michigan, Kevin LeachUniversity of Michigan, Zohreh SharafiUniversity of Michigan, Nicholas McKayUniversity of Michigan, USA, Tyler SantanderUniversity of California at Santa Barbara, Westley WeimerUniversity of Michigan, USA
DOI
01:37
1m
Talk
Does Stress Impact Technical Interview Performance?
Research Papers
Mahnaz BehrooziNorth Carolina State University, USA, Shivani ShirolkarNorth Carolina State University, USA, Titus BarikMicrosoft, USA, Chris ParninNorth Carolina State University, USA
DOI
01:39
1m
Talk
Reducing Implicit Gender Biases in Software Development: Does Intergroup Contact Theory Work?
Research Papers
Yi WangCoCo Labs, USA, Min ZhangEast China Normal University, China
DOI
01:41
19m
Talk
Conversations on Community
Paper Presentations
Kelly BlincoeUniversity of Auckland, Mahnaz BehrooziNorth Carolina State University, USA, Xin TanPeking University, China, Yi WangRochester Institute of Technology, Yu HuangUniversity of Michigan, M: Peter RigbyConcordia University, Montreal, Canada