  Background: Code review, the discussion around a code change among humans,
forms a communication network that enables its participants to exchange and
spread information. Although reported by qualitative studies, our understanding
of the capability of code review as a communication network is still limited.
Objective: In this article, we report on a first step towards evaluating the
capability of code review as a communication network by quantifying how fast
and how far information can spread through code review: the upper bound of
information diffusion in code review. Method: In an in-silico experiment, we
simulate an artificial information diffusion within large (Microsoft),
mid-sized (Spotify), and small code review systems (Trivago) modelled as
communication networks. We then measure the minimal topological and temporal
distances between the participants to quantify how far and how fast information
can spread in code review. Results: An average code review participants in the
small and mid-sized code review systems can spread information to between 72%
and 85% of all code review participants within four weeks independently of
network size and tooling; for the large code review systems, we found an
absolute boundary of about 11000 reachable participants. On average (median),
information can spread between two participants in code review in less than
five hops and less than five days. Conclusion: We found evidence that the
communication network emerging from code review scales well and spreads
information fast and broadly, corroborating the findings of prior qualitative
work. The study lays the foundation for understanding and improving code review
as a communication network.
