Kernel Newbies archive on
 help / color / Atom feed
From: "Valdis Klētnieks" <>
To: Irfan Ullah (울라 이르판) <>
Cc:, Ruben Safir <>,
Subject: Kernel development tools (was Re: Software Prefetching using Machine learning)
Date: Thu, 10 Oct 2019 01:51:00 -0400
Message-ID: <206965.1570686660@turing-police> (raw)
In-Reply-To: <>

[-- Attachment #1.1: Type: text/plain, Size: 816 bytes --]

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....

[-- Attachment #1.2: Type: application/pgp-signature, Size: 832 bytes --]

[-- Attachment #2: Type: text/plain, Size: 170 bytes --]

Kernelnewbies mailing list

  parent reply index

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

Reply instructions:

You may reply publically to this message via plain-text email
using any one of the following methods:

* Save the following mbox file, import it into your mail client,
  and reply-to-all from there: mbox

  Avoid top-posting and favor interleaved quoting:

* Reply using the --to, --cc, and --in-reply-to
  switches of git-send-email(1):

  git send-email \
    --in-reply-to=206965.1570686660@turing-police \ \ \ \ \ \

* If your mail client supports setting the In-Reply-To header
  via mailto: links, try the mailto: link

Kernel Newbies archive on

Archives are clonable:
	git clone --mirror kernelnewbies/git/0.git

	# If you have public-inbox 1.1+ installed, you may
	# initialize and index your mirror using the following commands:
	public-inbox-init -V2 kernelnewbies kernelnewbies/ \
	public-inbox-index kernelnewbies

Example config snippet for mirrors

Newsgroup available over NNTP:

AGPL code for this site: git clone