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As a maintainer of an open source software project, you are usually happyabout contributions in the form of pull requests that bring the project a stepforward. Past studies have shown that when reviewing a pull request, not onlyits content is taken into account, but also, for example, the socialcharacteristics of the contributor. Whether a contribution is accepted and howlong 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 frombots may be prioritized lower, even if the bots are explicitly deployed by thedevelopment team and are considered useful.  One goal of the bot research and development community is to design helpfulbots to effectively support software development in a variety of ways. To getcloser to this goal, in this GitHub mining study, we examine the measurabledifferences in how maintainers interact with manually created pull requestsfrom 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 takessignificantly longer for a bot pull request to be interacted with and for it tobe merged, even though they contain fewer changes on average than human pullrequests. These results suggest that bots have yet to realize their fullpotential.

Bots Don't Mind Waiting, Do They? Comparing the Interaction With Automatically and Manually Created Pull Requests