TAB self-nomination

TAB self-nomination

[Julia Lawall]

I'd like to nominate myself to serve on the TAB.

I have been developing and maintaining the C code transformation tool
Coccinelle since the mid 2000s, and have been contributing to the Linux
kernel since then, both with patches, and by pre-reviewing reports
generated by Coccinelle via 0-day.  More recently, I have been looking at
the Linux kernel task scheduler, both in terms of studying the performance
of applications induced by the scheduler as it evolves and in terms of
verification of the code that implements it.  I have given talks about the
scheduling work at various conferences.

My main interests in the context of the TAB are in helping develop
initiatives that improve code quality and code understandability.  In
particular, in my recent work on trying to understand the Linux kernel task
scheduler, I can see how the current strategies for documenting the source
code are not always at the right granularity to enable a newcomer to the
subsystem to understand the underlying design choices.  I hope to be able
to support initiatives for designing Linux kernel documentation,
formalization of the algorithms used in the code, introduction of safer
languages and coding styles, and approaches to understand the root causes
of performance issues and improvements.

Finally, my career has been spent in academia, and I have been very
grateful for the opportunity to contribute to and learn from the Linux
kernel community in this context.  Today is an exciting time of change in
software development due to the increasing capabilities of AI.  This is
currently being discussed in the kernel community, but is also the subject
of extensive research in academia, particularly in the software engineering
community.  Some of this research is already motivated by and evaluated on
the Linux kernel.  I hope to help provide a pathway for more direct and
fruitful collaboration between researchers and the Linux kernel community,
to help put ideas into practice, and to help inspire new research advances.

Julia Lawall

Re: TAB self-nomination

[Sasha Levin]

On Sat, Dec 13, 2025 at 08:42:21AM +0900, Julia Lawall wrote:
>I'd like to nominate myself to serve on the TAB.
>
>I have been developing and maintaining the C code transformation tool
>Coccinelle since the mid 2000s, and have been contributing to the Linux
>kernel since then, both with patches, and by pre-reviewing reports
>generated by Coccinelle via 0-day.  More recently, I have been looking at
>the Linux kernel task scheduler, both in terms of studying the performance
>of applications induced by the scheduler as it evolves and in terms of
>verification of the code that implements it.  I have given talks about the
>scheduling work at various conferences.
>
>My main interests in the context of the TAB are in helping develop
>initiatives that improve code quality and code understandability.  In
>particular, in my recent work on trying to understand the Linux kernel task
>scheduler, I can see how the current strategies for documenting the source
>code are not always at the right granularity to enable a newcomer to the
>subsystem to understand the underlying design choices.  I hope to be able
>to support initiatives for designing Linux kernel documentation,
>formalization of the algorithms used in the code, introduction of safer
>languages and coding styles, and approaches to understand the root causes
>of performance issues and improvements.
>
>Finally, my career has been spent in academia, and I have been very
>grateful for the opportunity to contribute to and learn from the Linux
>kernel community in this context.  Today is an exciting time of change in
>software development due to the increasing capabilities of AI.  This is
>currently being discussed in the kernel community, but is also the subject
>of extensive research in academia, particularly in the software engineering
>community.  Some of this research is already motivated by and evaluated on
>the Linux kernel.  I hope to help provide a pathway for more direct and
>fruitful collaboration between researchers and the Linux kernel community,
>to help put ideas into practice, and to help inspire new research advances.
>
>Julia Lawall

I've worked with Julia for over a decade now, and she's had a big impact on my
career and on me personally.

I first got to know Julia through Coccinelle. I thought that it's powered by
magic.

Julia brought up the idea of using machine learning to find patches that should
go to stable. That project became AUTOSEL, and it's helped us backport
thousands of fixes that would've been missed otherwise. Working with her taught
me a lot about taking research and making it useful for actual kernel work.

To me, Julia is a role model. She's always trying to help the people around
her. Through outreach, through mentoring, through research. She's impacted
hundreds of people in this community, directly and indirectly.

She takes the time with newcomers, and that matters. It mattered to me when I
was new.

I've been lucky to serve three terms on the TAB, and I want to thank everyone
for trusting me with that. I'm not running again, but I really hope Julia gets
a seat.

Julia, thank you.

-- 
Thanks,
Sasha

Re: TAB self-nomination

[Shuah]

On 12/12/25 17:38, Sasha Levin wrote:
> On Sat, Dec 13, 2025 at 08:42:21AM +0900, Julia Lawall wrote:
>> I'd like to nominate myself to serve on the TAB.

Awesome. We managed to convince you to throw your hat in the ring.

>>
>> I have been developing and maintaining the C code transformation tool
>> Coccinelle since the mid 2000s, and have been contributing to the Linux
>> kernel since then, both with patches, and by pre-reviewing reports
>> generated by Coccinelle via 0-day.  More recently, I have been looking at
>> the Linux kernel task scheduler, both in terms of studying the performance
>> of applications induced by the scheduler as it evolves and in terms of
>> verification of the code that implements it.  I have given talks about the
>> scheduling work at various conferences.
>>
>> My main interests in the context of the TAB are in helping develop
>> initiatives that improve code quality and code understandability.  In
>> particular, in my recent work on trying to understand the Linux kernel task
>> scheduler, I can see how the current strategies for documenting the source
>> code are not always at the right granularity to enable a newcomer to the
>> subsystem to understand the underlying design choices.  I hope to be able
>> to support initiatives for designing Linux kernel documentation,
>> formalization of the algorithms used in the code, introduction of safer
>> languages and coding styles, and approaches to understand the root causes
>> of performance issues and improvements.
>>
>> Finally, my career has been spent in academia, and I have been very
>> grateful for the opportunity to contribute to and learn from the Linux
>> kernel community in this context.  Today is an exciting time of change in
>> software development due to the increasing capabilities of AI.  This is
>> currently being discussed in the kernel community, but is also the subject
>> of extensive research in academia, particularly in the software engineering
>> community.  Some of this research is already motivated by and evaluated on
>> the Linux kernel.  I hope to help provide a pathway for more direct and
>> fruitful collaboration between researchers and the Linux kernel community,
>> to help put ideas into practice, and to help inspire new research advances.
>>
>> Julia Lawall
> 
> I've worked with Julia for over a decade now, and she's had a big impact on my
> career and on me personally.
> 
> I first got to know Julia through Coccinelle. I thought that it's powered by
> magic.
> 
> Julia brought up the idea of using machine learning to find patches that should
> go to stable. That project became AUTOSEL, and it's helped us backport
> thousands of fixes that would've been missed otherwise. Working with her taught
> me a lot about taking research and making it useful for actual kernel work.
> 
> To me, Julia is a role model. She's always trying to help the people around
> her. Through outreach, through mentoring, through research. She's impacted
> hundreds of people in this community, directly and indirectly.

I couldn't have said it better. Julia is my role model as well. She is ready
to help and truly cares for new developers, taking the time to help.

> 
> She takes the time with newcomers, and that matters. It mattered to me when I
> was new.
> 
> I've been lucky to serve three terms on the TAB, and I want to thank everyone
> for trusting me with that. I'm not running again, but I really hope Julia gets
> a seat.

Thank you Sasha - we are going to miss you on TAB. Hope you will come back to
serve in the future.

thanks,
-- Shuah