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From: "Valdis Klētnieks" <valdis.kletnieks@vt.edu>
To: Irfan Ullah (울라 이르판) <irfan@dke.khu.ac.kr>
Cc: greg@kroah.com, Ruben Safir <ruben@mrbrklyn.com>,
	kernelnewbies@kernelnewbies.org
Subject: Kernel development tools (was Re: Software Prefetching using Machine learning)
Date: Thu, 10 Oct 2019 01:51:00 -0400	[thread overview]
Message-ID: <206965.1570686660@turing-police> (raw)
In-Reply-To: <CA+mB8OwaC1ZQeX-KHTPeSG00AKE9Jy3mwwDUx15W-uttn9d+PQ@mail.gmail.com>


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On Thu, 10 Oct 2019 11:48:11 +0900, Irfan Ullah said:
> @All,* There is one thing I want to share, although it is not too relevant
> but worth to share,*  that very limited number of *easy-to-use-&-understand*
> tools and libraries available to welcome  and facilitate the
> newbies/freshmen in the kernel development as compare to other development
> environments.

Well... for better or worse, the Linux kernel is an environment where
programmers are expected to have a fairly good grasp on programming and
software development already, and can figure most things out on their own.

Having said that, if you have specific suggestions of tools and libraries that
would make a difference, feel free to state what you think is missing - there's
a good chance that it actually exists but you didn't know about it....


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  parent reply	other threads:[~2019-10-10  5:51 UTC|newest]

Thread overview: 12+ messages / expand[flat|nested]  mbox.gz  Atom feed  top
2019-10-09  3:37 Software Prefetching using Machine learning Irfan Ullah (울라 이르판)
2019-10-09  7:44 ` Greg KH
2019-10-09 19:08 ` Valdis Klētnieks
2019-10-10  0:21   ` Ruben Safir
2019-10-10  0:24   ` Ruben Safir
2019-10-10  2:10     ` Irfan Ullah (울라 이르판)
2019-10-10  2:48       ` Irfan Ullah (울라 이르판)
2019-10-10  5:43         ` Valdis Klētnieks
2019-10-10  5:51         ` Valdis Klētnieks [this message]
2019-10-10  6:21           ` Kernel development tools (was Re: Software Prefetching using Machine learning) Irfan Ullah (울라 이르판)
2019-10-10  6:40             ` Greg KH
2019-10-10 13:22       ` Software Prefetching using Machine learning Rik van Riel

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