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Message-ID: <CAPt3h3XTjAY5v-_-VB2ud8wHQUDcRe8hjhHzW+03=j08zPbh6w@mail.gmail.com>
Date:   Sat, 25 Aug 2018 09:29:22 +0800
From:   xin tan <tanxin0725@...il.com>
To:     linux-kernel@...r.kernel.org
Subject: Ask for your comment for our research: Reducing the Workload of the
 Linux Kernel Maintainers: Multiple-Committer Model

Hi all,
I am a Ph.D. student from China. Our research team is dedicated to
helping FLOSS ecosystems have healthy and sustainable development. The
Linux kernel is one of the key study cases for us because as a
prominent FLOSS project, the Linux kernel has many unique practices.
Recently, we observed that increasing numbers of contributors to the
Linux kernel have concerns regarding whether the development process
(workflow) can handle the current mass of patches and even more
patches in the future. While the workflow gives maintainers many
rights, it also places significant pressure on them, which bears the
risk of a single point of failure. We investigated the effect of a new
model, the multiple-committer model, which is currently used by the
i915 subsystem to alleviate the burden on its maintainer. We find that
this model can reduce the proportion of the review workload of the
busiest maintainer, reduce the review latency and maintainers'
overwork, and simplify the review network. The review process is
strictly enforced to guarantee the quality of patches. Subsystems with
usage demands, mechanisms for ensuring patch quality, and candidate
committers are suitable for the model. Sufficient precommit testing, a
strict review process, necessary documentation, and the use of
automatic tools are important practices to follow when applying the
model.
We hope our work would help other subsystems extract valuable
information and optimize their workflow to achieve a more efficient
review process and sustain themselves in a constantly changing,
complicated environment. We uploaded the draft paper at
"https://github.com/SunflowerPKU/Reducing-the-Workload-of-the-Linux-Kernel-Maintainers-Multiple-Committer-Model/blob/master/reduce-workload-linux.pdf".
If you are interested in this topic, please take a moment to
understand our work. We are looking forward to your comments and
suggestions.

Best regard,
Xin Tan

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