[openstack-dev] [nova] Risk prediction model for OpenStack
林泽燕
linzeyan at pku.edu.cn
Thu Apr 6 06:09:16 UTC 2017
Hi, Matt,
Thank you for your attention. The information you provided is very helpful.
Best Regards
> -----原始邮件-----
> 发件人: "Matt Riedemann" <mriedemos at gmail.com>
> 发送时间: 2017-04-05 23:33:21 (星期三)
> 收件人: openstack-dev at lists.openstack.org
> 抄送:
> 主题: Re: [openstack-dev] [nova] Risk prediction model for OpenStack
>
> On 4/5/2017 9:00 AM, Jeremy Stanley wrote:
> > On 2017-04-05 14:00:59 +0800 (+0800), 林泽燕 wrote:
> > [...]
> >> I wonder if I could show you my study, including some metrics for
> >> the prediction model and a visualization tool.
> > [...]
> >
> > I want to start out thanking you for your research and interest in
> > OpenStack's development practices. I love that our contribution
> > model enables such scientific analysis, a sometimes less recognized
> > benefit of our community's choice to work entirely in the open. This
> > specific study is also very insightful and well-presented.
> >
> >> In this release, 36 developers left the development of this file
> >> (they made contributions in last release but not this one).
> >> Developers leaving a code file deprive the file of the knowledge
> >> of the decisions they have made.
> > [...]
> >
> > One potentially influential aspect of our development model is that
> > we place a heavy importance on code review. For any patch to make it
> > into a branch under official revision control, it must first be
> > reviewed by multiple experienced, long-standing contributors to that
> > repository. Our hope is that even though some developers may cease
> > contributing new patches to a file, some of them would still be
> > reviewing, guiding and refining changes proposed by newer
> > contributors. It doesn't seem like this behavior was captured in
> > your analysis, or alternatively the fact that your model yielded
> > relatively accurate predictions could imply that our review process
> > has little impact on defects introduced by new commits.
> >
> > If you do at some point wish to try integrating review metrics into
> > your analysis, our code review system has a REST API you can
> > leverage, and much of the data you'd likely be interested in can be
> > queried via anonymous methods such that you wouldn't even need to
> > create an account. Documentation for the interface is available at
> > https://review.openstack.org/Documentation/rest-api.html and we also
> > have documentation of our general developer workflow at
> > https://docs.openstack.org/infra/manual/developers.html as well as
> > some background on our development model at
> > https://docs.openstack.org/project-team-guide/open-development.html
> > if that helps.
> >
>
> Jeremy pointed out what I was going to mention, which was the lack of
> input on code reviews. Each major component of Nova, or virt drivers,
> generally have subteams, or some sort of subject domain expert, that is
> consulted or at least involved in reviewing code contributions. So while
> they may not be making the changes themselves to a component, they
> should be reviewing those changes. For example, with the
> nova/virt/libvirt/driver.py, danpb was the main core reviewer and
> maintainer for that code in the past, so while he didn't write
> everything, he was reviewing a lot of the contributions.
>
> Some of the files are also skewed a bit, and you might want to take into
> account logic paths in a module to exclude it. For example, exception.py
> and the various opts.py modules are outliers. They are basically files
> that contain constants but not logic code so the chance of those having
> an actual owner is small, but so should be the risk for bugs. They will
> also have a high diversity given how common they are.
>
> I'm not sure I understood the timeline graphs, or the point those are
> making. We definitely have an ebb and flow of contributions based on the
> release schedule where feature development and new code is loaded toward
> the front of the release, and then that is supposed to be cut off toward
> the 3rd milestone at the end of the release so we can stabilize and
> focus on bugs.
>
> In general some of this is common sense. When one person "owns" most of
> a module in a piece of software they are the expert and therefore bugs
> due to lack of understanding the bigger picture of that module, or how
> it fits into the bigger system, should be mitigated. When that person
> leaves, if others on the team don't have the domain knowledge, there are
> going to be mistakes. We definitely have parts of the nova codebase that
> fall into areas that we know are just very touchy and error prone and we
> avoid changing those if at all possible (block device mappings, quotas,
> neutronv2.api, nova-network and cells v1 come to mind). This is hard in
> a big open source project, but is also why we have high standards for
> core reviewers (those that can approve code contributions) and a
> ridiculous amount of continuous integration testing.
>
> --
>
> Thanks,
>
> Matt
>
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Best regards!
——————————
Zeyan Lin
Department of Computer Science
School of Electronics Engineering & Computer Science
Peking University
Beijing 100871, China
E-mail:linzeyan at pku.edu.cn
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