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“Was my contribution fairly
reviewed”
A framework to study the perception of fairness in
modern code reviews
Daniel M German
University of Victoria
dmg@uvic.ca
http://github.com/dmgerman/papers
What does it mean to be fair?
Is ICSE fair?
62% of reviews were considered to be fair (2017)
Is ICSE fair?
62% of reviews were considered to be fair (2017)
48% (for rejected papers)
Is ICSE fair?
ICSE experiments
ICSE experiments
• 2016 and before:
ICSE experiments
• 2016 and before:
• Introduction of a Program Board
ICSE experiments
• 2016 and before:
• Introduction of a Program Board
• Rebuttal period
ICSE experiments:
ICSE experiments:
• 2017
ICSE experiments:
• 2017
• Structured reviews
ICSE experiments:
• 2017
• Structured reviews
• Reviewers were anonymous among PC
ICSE experiments:
• 2017
• Structured reviews
• Reviewers were anonymous among PC
• Public “Reviewer guidelines”
ICSE experiments:
• 2017
• Structured reviews
• Reviewers were anonymous among PC
• Public “Reviewer guidelines”
• No “subreviewer” (e.g reviews done by students)
ICSE experiments:
• 2017
• Structured reviews
• Reviewers were anonymous among PC
• Public “Reviewer guidelines”
• No “subreviewer” (e.g reviews done by students)
• No list of research topics
ICSE experiments
ICSE experiments
• 2018
ICSE experiments
• 2018
• Gender balance of PC
ICSE experiments
• 2018
• Gender balance of PC
• Double blind
ICSE experiments
• 2018
• Gender balance of PC
• Double blind
• Authors received numerical scores
What is ICSE trying to solve?
What is ICSE trying to solve?
• Inconsistency of reviewing
What is ICSE trying to solve?
• Inconsistency of reviewing
• Bias
What is ICSE trying to solve?
• Inconsistency of reviewing
• Bias
• Topic
What is ICSE trying to solve?
• Inconsistency of reviewing
• Bias
• Topic
• Interpersonal
What is ICSE trying to solve?
• Inconsistency of reviewing
• Bias
• Topic
• Interpersonal
• Lack of transparency
What is ICSE trying to solve?
• Inconsistency of reviewing
• Bias
• Topic
• Interpersonal
• Lack of transparency
The ICSE reviewer lottery
What is ICSE trying to solve?
• Inconsistency of reviewing
• Bias
• Topic
• Interpersonal
• Lack of transparency
The ICSE reviewer lottery
Some participants consider the process unfair
Participants are likely to leave a
system if they perceive it to be
unfair
What does it mean to be fair?
What does it mean to be
treated fairly?
Fairness
Fairness
• Also called “Justice”
Fairness
• Also called “Justice”
• Concept from:

• Philosophy/Law/Psychology/
Sociology/Management/
Economics…
Fair (Merriam Webster):
Fair (Merriam Webster):
1.
Fair (Merriam Webster):
1.
a. Marked with impartiality and
honesty: free from self-interest,
prejudice, or favouritism
Fair (Merriam Webster):
1.
a. Marked with impartiality and
honesty: free from self-interest,
prejudice, or favouritism
b. Conforming with the established
rules
Justice (Merriam-Webster):
Justice (Merriam-Webster):
1.
Justice (Merriam-Webster):
1.
a. The maintenance or administration
of what is just, specially by the
impartial adjustment of conflicting
claims or the assignment of
merited rewards or punishments
Justice (Merriam-Webster):
Justice (Merriam-Webster):
2.
Justice (Merriam-Webster):
2.
a. The quality of being just,
impartial or fair
Organizational Fairness/Justice:
Organizational Fairness/Justice:
‣ how to decide and allocate
Organizational Fairness/Justice:
‣ how to decide and allocate
‣ resources and decisions
Organizational Fairness/Justice:
‣ how to decide and allocate
‣ resources and decisions
‣ in a way that is fair and just
Organizational Fairness/Justice:
‣ how to decide and allocate
‣ resources and decisions
‣ in a way that is fair and just
‣ to the individuals and the group as a
whole.
In general, we care about fairness
when somebody makes a decision
that affects us.
Fairness theory “focuses on explaining
when authorities should be held
accountable for unfavourable events”
How to increase the
perception of fairness?
Distributive Fairness
Distributive Fairness
Outcomes are allotted
Distributive Fairness
Outcomes are allotted
to persons
Distributive Fairness
Outcomes are allotted
to persons
whose relative shares
Distributive Fairness
Outcomes are allotted
to persons
whose relative shares
can be described by some functional rule
Distributive Fairness
Outcomes are allotted
to persons
whose relative shares
can be described by some functional rule
and some standard
Distributive Fairness
Distributive Fairness
• Should those that contribute more
receive more?
Distributive Fairness
• Should those that contribute more
receive more?
• How do you measure contribution?
Distributive Fairness
• Should those that contribute more
receive more?
• How do you measure contribution?
• Is there a minimal standard defined in
the system?
Equity vs Equality
Equity vs Equality
• Equity:

• Those that contribute more should
receive more
Equity vs Equality
• Equity:

• Those that contribute more should
receive more
• Equality:

• Everybody deserves the same
Organizations favour equity
Organizations favour equity
• Rewards those that contribute more
• Improves performance

Newcomers are special case
Newcomers are special case
• Ok to have a positive bias to
newcomers

• They have not yet contributed

Procedural Fairness
Procedural Fairness
• Concerned with the rules/process of making a decision:
Procedural Fairness
• Concerned with the rules/process of making a decision:
• Consistency of decisions across time
Procedural Fairness
• Concerned with the rules/process of making a decision:
• Consistency of decisions across time
• Bias suppression of decision makers
Procedural Fairness
• Concerned with the rules/process of making a decision:
• Consistency of decisions across time
• Bias suppression of decision makers
• Accuracy of information used in decisions
Procedural Fairness
• Concerned with the rules/process of making a decision:
• Consistency of decisions across time
• Bias suppression of decision makers
• Accuracy of information used in decisions
• Control: those affected should have a voice
Procedural Fairness
• Concerned with the rules/process of making a decision:
• Consistency of decisions across time
• Bias suppression of decision makers
• Accuracy of information used in decisions
• Control: those affected should have a voice
• Correctability: there should exist an appeal process
Procedural Fairness
• Concerned with the rules/process of making a decision:
• Consistency of decisions across time
• Bias suppression of decision makers
• Accuracy of information used in decisions
• Control: those affected should have a voice
• Correctability: there should exist an appeal process
• Ethicality: the process upholds personal and organizational
standards
Interactional fairness
Interactional fairness
• Individuals are not only concerned with outcomes but how
they are treated
Interactional fairness
• Individuals are not only concerned with outcomes but how
they are treated
• Respect: actions and signals that reflect the intrinsic value
that a person has for another
Interactional fairness
• Individuals are not only concerned with outcomes but how
they are treated
• Respect: actions and signals that reflect the intrinsic value
that a person has for another
• No rudeness/berating/sexism/racism
Interactional fairness
• Individuals are not only concerned with outcomes but how
they are treated
• Respect: actions and signals that reflect the intrinsic value
that a person has for another
• No rudeness/berating/sexism/racism
• Invasion of privacy: no disclosure of secrets/improper
questions
Interactional fairness
• Individuals are not only concerned with outcomes but how
they are treated
• Respect: actions and signals that reflect the intrinsic value
that a person has for another
• No rudeness/berating/sexism/racism
• Invasion of privacy: no disclosure of secrets/improper
questions
• Psychological safety: no increase of stress
Informational fairness
Informational fairness
• What information is used/exchanged is important
Informational fairness
• What information is used/exchanged is important
• Truthfulness:
Informational fairness
• What information is used/exchanged is important
• Truthfulness:
• Avoid deception: people don’t like to be “lied to”
Informational fairness
• What information is used/exchanged is important
• Truthfulness:
• Avoid deception: people don’t like to be “lied to”
• Adequacy of explanations:
Informational fairness
• What information is used/exchanged is important
• Truthfulness:
• Avoid deception: people don’t like to be “lied to”
• Adequacy of explanations:
• Reasonable explanations help accepting an
outcome
Code Reviews
Code Reviews
• A decision process that involves
individuals
Code Reviews
• A decision process that involves
individuals
• Prone to fairness concerns
Distributive Fairness
Distributive Fairness
• Two concerns:
Distributive Fairness
• Two concerns:
• Patch level
Distributive Fairness
• Two concerns:
• Patch level
• Individual level
Patches
Patches
• Equity: Some patches
Patches
• Equity: Some patches
• are more important than others
Patches
• Equity: Some patches
• are more important than others
• require more than others
Patches
• Equity: Some patches
• are more important than others
• require more than others
• Need: what is the minimal treatment
that a patch should receive?
Distributive Fairness: individuals
Distributive Fairness: individuals
• Equity vs Equality
Distributive Fairness: individuals
• Equity vs Equality
• Should core developers receive
preferential treatment?
Distributive Fairness: individuals
• Equity vs Equality
• Should core developers receive
preferential treatment?
• Newcomers:
Distributive Fairness: individuals
• Equity vs Equality
• Should core developers receive
preferential treatment?
• Newcomers:
• What preferential treatment should they
get?
Procedural Fairness
Consistency and bias suppression
Consistency and bias suppression
• Define:
Consistency and bias suppression
• Define:
• standards of quality and minimal
requirements for approved patches
Consistency and bias suppression
• Define:
• standards of quality and minimal
requirements for approved patches
• prioritization strategies
Control and Inf. Accuracy
Control and Inf. Accuracy
• Allow authors and non-reviewers to
comment on patches under review

Correctability
Correctability
• Create an appeal process for
rejected patches

Ethicallity
Ethicallity
• Define ethical standards on how
code reviews should be done
Ethicallity
• Define ethical standards on how
code reviews should be done
• What is Conflict of Interest?
Ethicallity
• Define ethical standards on how
code reviews should be done
• What is Conflict of Interest?
• Is self-reviewing allowed?
Interactional Fairness
Interactional Fairness
• Define a code of conduct

Equity vs Equality
Equity vs Equality
• A code of conduct seems to imply
that everybody is equal
Equity vs Equality
• A code of conduct seems to imply
that everybody is equal
• But in reality, some people are more
important than others
Informational Fairness
Truthfulness
Truthfulness
• Do code reviews with full ongoing
transparency

Adequacy
Adequacy
• Reviewers should:
Adequacy
• Reviewers should:
• provide good feedback
Adequacy
• Reviewers should:
• provide good feedback
• explain delays, and
Adequacy
• Reviewers should:
• provide good feedback
• explain delays, and
• unexpected treatments.
Empirical Study
OpenStack
OpenStack
• Ecosystem of 30-something projects
OpenStack
• Ecosystem of 30-something projects
• Industrial
OpenStack
• Ecosystem of 30-something projects
• Industrial
• Most contributions are by paid developers
OpenStack
• Ecosystem of 30-something projects
• Industrial
• Most contributions are by paid developers
• 0.5 M SLOCs by 60k contributors
OpenStack
• Ecosystem of 30-something projects
• Industrial
• Most contributions are by paid developers
• 0.5 M SLOCs by 60k contributors
• Using code reviews
Survey
Survey
• 2870 invitations
Survey
• 2870 invitations
• 7.4% response rate (213)
Have your contributions being treated unfairly?
0
10
20
30
40
Never Rarely Occassionally Often Always
According to your experience as a reviewer, do
you perform code reviews unfairly?
0
15
30
45
60
Never Rarely Occassionally Often Always
How do you prioritize reviews?
Open ended answers
Open ended answers
Open ended answers
Some open-ended answers
Equity vs Equality
“A submitter is presented with the
illusion that all submissions are equal,
when in reality the community prioritizes
[code reviews] from known submitters”
Newcomers
“I have only tried to make one
contribution. I was so discouraged by
the response from the reviewer I have
not tried again.”
Consistency
“I have contributed and reviewed in 3
projects: [A, B] and [C]. I found that [A]
and [B] to be quite reasonable and fair.
As stated above, [C] is a disaster.”
Control and Correctability
“[A] core reviewer gave me a -1 which
was not understandable. I asked 4 time
on IRC to discuss it and he ignored
me”
Ethicallity
“People look out for friends instead of
looking out for their projects”
Interactional Fairness
“Contributions are ignored unless I beg
for attention. I might have to contribute a
minor improvement. I never have time
to beg for attention. If you don’t want
my help, I got the message loud and
clear”
OpenStack: Summary
OpenStack: Summary
• Overall, it seems to be perceived as
fair
OpenStack: Summary
• Overall, it seems to be perceived as
fair
• There are signs of discontent,
specially in some sub-projects
Takeaway message
Takeaway message
Fairness is an issue that needs
attention in code reviews
Takeaway message
Fairness is an issue that needs
attention in code reviews
This framework helps understand what
are the issues and how to address
them
To summarize
http://turingmachine.org
http://github.com/dmgerman/papers

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