  As a maintainer of an open source software project, you are usually happy
about contributions in the form of pull requests that bring the project a step
forward. Past studies have shown that when reviewing a pull request, not only
its content is taken into account, but also, for example, the social
characteristics of the contributor. Whether a contribution is accepted and how
long this takes therefore depends not only on the content of the contribution.
What we only have indications for so far, however, is that pull requests from
bots may be prioritized lower, even if the bots are explicitly deployed by the
development team and are considered useful.
  One goal of the bot research and development community is to design helpful
bots to effectively support software development in a variety of ways. To get
closer to this goal, in this GitHub mining study, we examine the measurable
differences in how maintainers interact with manually created pull requests
from humans compared to those created automatically by bots.
  About one third of all pull requests on GitHub currently come from bots.
While pull requests from humans are accepted and merged in 72.53% of all cases,
this applies to only 37.38% of bot pull requests. Furthermore, it takes
significantly longer for a bot pull request to be interacted with and for it to
be merged, even though they contain fewer changes on average than human pull
requests. These results suggest that bots have yet to realize their full
potential.
