EDedflsafoiewq·Oct 24, 2018
An interesting prospect, but the patches appear to consist mostly of wrapping a block of code that throws a NullPointerException in a check for null. This is non-trivial -- consider https://github.com/aaime/geowebcache/pull/1/files, where the initializer form has to be broken up and the bot needs some kind of knowledge of data dependencies to know how much code to wrap in the if-block -- but it is also help that humans already receive from machines in the form of lints.
Much more interesting is this: https://github.com/eclipse/ditto/pull/151/files. How did it know to use this.isConsuming()?
Here's the list of PRs it made: https://github.com/Spirals-Team/repairnator/issues/758
I want to take issue with a quote from the paper:
> There is one more aspect to consider. It has been shown that human engineers do not accept con
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tributions from bots as easily as contributions from other humans, even if they are strictly identical [5]. The reason is that humans tend to have a priori biases against machines, and are more tolerant to errors if the contribution comes from a human peer.
Even if a machine and a human submit the exact same patch, the human's carries the implicit promise that it was the result of a (more or less :) intelligent process. The human actually thought about it and came to the conclusion that not only did it make the build pass but that it was, taking into account as much context as might be necessary, the right patch to make. If you review a machine's patch, you are obliged to perform the whole intelligent evaluation of whether it is the right patch yourself, which is almost never easier than simply writing the patch yourself.