[GSOC] "Project: Improve inter-procedural analyses and optimisations"

Hi all,

My name is Fahad Nayyar. I am an undergraduate student from India.

I am interested to participate in GSOC under the project “Improve inter-procedural analyses and optimizations”.

I have been using LLVM for the past 8 months. I have written various intra-procedural analysis in LLVM as FunctionPass for my course projects and research projects. But I’ve not contributed to the LLVM community yet. I am very excited to contribute to LLVM!

I am not too familiar with the inter-procedural analysis infrastructure of LLVM. I have written small toy inter-procedural dataflow analysis (like taint analysis, reaching definitions, etc) for JAVA programs using SOOT tool [5]. I am familiar with the theory of inter-procedural analysis (I’ve read some chapters of [1], [2] and [3] for this).

I am trying to understand the LLVM’s Attributor framework. I am interested in these 3 aspects:

  1. How Attributor can help for standard inter-procedural and intra-procedural analysis passes of LLVm. I’ve seen the tutorial [4]. I would like to discuss ways of improving other optimization passes similarly (or some examples which have already been implemented).

  2. Improve dynamic memory related capabilities of Attributor. For example Improve HeapToStackConversions. Maybe such deductions can help safety (dis)provers. For example, can we improve the use-after-free bug detection using some attributes?

  3. Improve Liveness related capabilities of Attributor. Again I want to consider whether some attribute deduction can help liveness (dis)provers. For example NoReturn, WillReturn can be improved. I am sure these 2 attributes do not cover all the cases as it is an undecidable problem. But I was wondering whether there is room for improvement in their deduction mechanism.

  4. Can we optimize the attribute deduction algorithm to reduce compile time?

  5. Is there any attribute that tells whether a function has side-effects (does it always gives the same output for the same input? Or does it affect some global variable directly or indirectly?)?

It would be great if Johannes can provide me some TODOs before submitting my proposal. Also please tell some specific IPO improvement goals which you have in mind for this project. I would be most interested in memory-related attributes, liveness deductions from attributes and measurable better IPO using attribute deduction.

Thanks and Regards.

References:

[1] Principles of Program Analysis.

[2] Data Flow Analysis: Theory and Practice.

[3] Static Program Analysis.

[4] 2019 LLVM Developers’ Meeting: J. Doerfert “The Attributor: A Versatile Inter-procedural Fixpoint…"

[5] Soot - A Java optimization framework

Hi Fahad,

We’re all happy to see you being interested in LLVM! More so in the Attributor! I’m a relatively new contributor so I
think I can help. Please note that the Attributor, apart from Johannes (who CC’d), has at least another 2 great
contributors, Hideto and Stefan (who I also CC’d). They were among the initial creators.

In the rest of this post I’ll try to help you familiarize yourself with the Attributor and maybe answer your questions.
Johannes can then give you specific things to do to get started.

Starting off, understanding the theory of data-flow analysis can help. I’d say don’t get too hang up on it, you just
have to understand the idea of fix-point analyses.

I don’t how much you know about the Attributor, so I’ll defer a too long (or too beginner) description because you might already know
a lot of things. You can of course any specific questions you want:
A summary is:
The Attributor tries to deduce attributes in different points of an LLVM IR program (you can see that in the video).
The deduction of these attributes is inter-connected, which is the whole point of the Attributor. The attributes
“ask” one another for information. For example, one attribute tries to see if a load loads from null pointer.
But the pointer operand might be non-constant (like %v in LLVM IR). Well, another attribute, whose job is to do value simplification
(i.e. constant folding / propagation etc.) might have folded that (%v) into the constant null. So, the former can ask him.
These connections give the power and the complexity.

The attributes have a state, that changes. When the state stops changing, it has reached a fixpoint, at which point
the deduction of it stops. From the initialization of the attribute until a fixpoint is reached, the state changes
in updates (called updateImpl() in the source code). This is where attributes try to deduce new things, ask one another
and eventually try to reach a fixpoint.

Finally, a fixpoint can be enforced. Because if we for some reason never stop changing, it would run forever.
Note however that attributes should be programmed in a way that fixpoint should be able to be reached
(This is where theory might help a little).

I’d suggest that you try to run the Attributor and follow a specific attribute’s updates and see what it tries to deduce.
That is, see its updateImpl(). With a couple of prints you can get a good idea of what it does and what info it
gets from other attributes (and when it stops). You can of course ask us if you’re interested in a specific one, if
there’s something you don’t understand etc.

Now, to (try to) answer your questions and hopefully other people can help.

How Attributor can help for standard inter-procedural and intra-procedural analysis passes of LLVm. I’ve seen the tutorial [4]. I would like to discuss ways of improving other optimization passes similarly (or some examples which have already been implemented).

The Attributor AFAIK is self-contained. It’s not in “production” yet and so it’s not connected with other passes. At this point, LLVM is focused on heavy inlining, which while very useful, you’ll lose a lot of the interprocedural information.
Note that there are other transforms that do Inter-Procedural Optimization (https://github.com/llvm/llvm-project/tree/master/llvm/lib/Transforms/IPO) but they don’t follow the idea of the Attributor.
But they might follow a fix-point analysis.

Improve dynamic memory related capabilities of Attributor. For example Improve HeapToStackConversions. Maybe such deductions can help safety (dis)provers. For example, can we improve the use-after-free bug detection using some attributes?
Stefan should know more about H2S. Regarding the use-after-free, I don’t think there’s currently any plans for it directly, but they can be I assume.

Improve Liveness related capabilities of Attributor. Again I want to consider whether some attribute deduction can help liveness (dis)provers. For example NoReturn, WillReturn can be improved. I am sure these 2 attributes do not cover all the cases as it is an undecidable problem. But I was wondering whether there is room for improvement in their deduction mechanism. Liveness is certainly something that we’re currently trying to improve and I don’t think we’ll ever stop. Most of the attributes interact with the deadness attribute (AAIsDead) both for asking it info and providing it info (i.e. the undefined-behavior attribute hopefully will at some point be able to tell AAIsDead that a block is dead because it contains UB). > Is there any attribute that tells whether a function has side-effects (does it always gives the same output for the same input? Or does it affect some global variable directly or indirectly?)? No AFAIK, although you might be interested in this: https://reviews.llvm.org/D74691#1887983

I hope this was helpful! Don’t hesitate to ask any questions.

Kind regards,
Stefanos Baziotis

Στις Παρ, 13 Μαρ 2020 στις 10:25 μ.μ., ο/η Fahad Nayyar via llvm-dev <llvm-dev@lists.llvm.org> έγραψε:

Dear Stefanos,

Thanks for such a quick response! And thanks for answering my questions!

Starting off, understanding the theory of data-flow analysis can help.

I know about some standard fix-point lattice-based data flow analysis like reaching definitions, live variable analysis, etc. I have done a course on “Program analysis” at my college.

The deduction of these attributes is inter-connected, which is the whole point of the Attributor.

Thanks for explaining this part with the example!

I’d suggest that you try to run the Attributor and follow a specific attribute’s updates and see what it tries to deduce. That is, see its updateImpl().

Thanks for suggesting this! I will try to do this and get back to you.

At this point, LLVM is focused on heavy inlining, which while very useful, you’ll lose a lot of the interprocedural information.

I see. It would be great if we can come up with some specific examples where using these deduced attributes can improve existing inter and intra procedural optimization passes. I am very interested to work towards exploring this potential of Attributor. So I would try to include such examples in my GSOC proposal.

Liveness is certainly something that we’re currently trying to improve and I don’t think we’ll ever stop.

It would be great if you can share some of the ongoing issues or discussion regarding improving Liveness information deduction using Attributor.

Thanks and regards

Fahad Nayyar

Hi Farad,

Thanks for such a quick response! And thanks for answering my questions! > Thanks for explaining this part with the example! > Thanks for suggesting this! I will try to do this and get back to you. No problem, always here to help. Let me reiterate: Don’t hesitate to ask questions as you progress! My description I hope was useful to get started but it’s certainly not enough (talking from experience). > I know about some standard fix-point lattice-based data flow analysis like… That’s good, it’s useful. > I see. It would be great if we can come up with some specific examples where using these deduced attributes can improve existing inter and intra procedural optimization passes. I am very interested to work towards exploring this potential of Attributor. I think everyone involved in the Attributor, in one way or another, thinks about how other analyses can benefit from it. So, yeah, you’re welcome. :slight_smile: Also, probably this will be a very interesting panel discussion for you: https://www.youtube.com/watch?v=cC2cspQgSxM > It would be great if you can share some of the ongoing issues or discussion regarding improving Liveness information deduction using Attributor. I’ll refrain from doing that right now, mainly because I’m afraid that I may lead you to a wrong direction (or too soon at least). So, let’s wait for Johannes to get in touch and we will certainly discuss it. I’d suggest that we try to familiarize yourself with the Attributor in the meantime, which is a certainly important immediate goal. Best, Stefanos Baziotis

Στις Σάβ, 14 Μαρ 2020 στις 12:05 π.μ., ο/η Fahad Nayyar <fahad17049@iiitd.ac.in> έγραψε:

Hi Fahad,

Improve dynamic memory related capabilities of Attributor. For example Improve HeapToStackConversions. Maybe such deductions can help safety (dis)provers. For example, can we improve the use-after-free bug detection using some attributes?
Stefan should know more about H2S. Regarding the use-after-free, I don’t think there’s currently any plans for it directly, but they can be I assume.

You are somewhat right. However, H2S is not about ‘use-after-free’ bug detection, but rather its prevention. We already do this, see example.

In the rest of this post I’ll try to help you familiarize yourself with the Attributor and maybe answer your questions.
Johannes can then give you specific things to do to get started.

In the meantime you could look at some TODOs in the Attributor itself and try those you see fit.

If you have any questions, don’t hesitate to ask.

-stefan

Dear Stefan and Stefanos,

Thanks for your suggestions!

I’d suggest that you try to run the Attributor and follow a specific attribute’s updates and see what it tries to deduce. That is, see its updateImpl(). With a couple of prints you can get a good idea of what it does and what info it gets from other attributes (and when it stops).

I tried to do this for the NoUnwind attribute. I printed getState(), isAssumedNoUnwind(), isKnownNoUnwind() in updateImpl method of classes AANoUnwind and AANoUnwindCallSite. I run the tests in nounwind.ll (/llvm/test/Transforms/Attributor/nounwind.ll). I used this command to run the test: “opt -attributor -attributor-disable=false nounwind.ll -S &> nounwind_out.ll”. But After seeing the output I was not able to understand how the attribute is changing for the tests. Its status was almost constant every time updateimp was called. Please tell me what other things should I try to print to better observe how the NoUnwind attribute is changing over the iterations of fix point analysis. Also please verify whether I am using the correct command to run the tests.

Also, probably this will be a very interesting panel discussion for you: https://www.youtube.com/watch?v=cC2cspQgSxM

Thanks for suggesting this! I watched the video and now I understand the pros and cons of inlining. But I still think that It would take me a while before I can come up with a very good example demonstrating the use of of of the Attribues in some IPO pass. I know how in [1] Johaanes explained the use of MaxObjSize and Dereferenceable in the AliasAnalysis. But I would be happy if I could come up with some even better example.

You are somewhat right. However, H2S is not about ‘use-after-free’ bug detection, but rather its prevention. We already do this, see example.

Thanks for sharing the example. Just for clarification, was this example demonstrating the point that we can automatically correct use-after-free bugs using attributes? If yes, then I didn’t understand how and which attribute helped in this correction? Also is it not wrong to change the IR as in this example? Replacing %1 = tail call noalias i8* @malloc(i64 4) ; tail call void @no_sync_func(i8* %1) with %1 = alloca i8, i64 4 solved the use-after-free bug, but doesn’t it also change the semantic of the program?

In the meantime you could look at some TODOs in the Attributor itself and try those you see fit.

I looked up some of the TODOs. I found AAReachability a very interesting attribute. I can start with TODO at line no. 2605 // TODO: Return the number of reachable queries. I can work towards this TODO. But I first want your advice on whether it looks doable for me. I can see that implementation of AAReachability attribute is not complete yet. I can try to learn more about it from D70233 and D71617.

I am trying to get more familiar with Attributor’s code. Since the code is very large right now, I thought to refer to some of the very initial patches of attributor (D59918, D60012, D63379). I believe that by looking at these three I can get a better idea of the framework as a whole. Please suggest if this is a good idea or not. Also please suggest any other way by which I can improve my understanding of the code.

I can see that Johanned have put up some issues for GSOC aspirants. I think that [2] ([Attributor] Cleanup and upstream Attribute::MaxObjectSize) will be a very good issue for me, It seems doable and I can get familiar with the whole process of writing a patch for an issue. How should I indicate to the community that I have started working towards this issue (should I comment on the issue page on github?)? I can try to work on AAReachability TODO after solving this issue.

Thanks and Regards

References

[1] https://youtu.be/HVvvCSSLiTw

[2] https://github.com/llvm/llvm-project/issues/179

Hi Farad,

I tried to do this for the NoUnwind attribute Hmm, I don’t have experience with this attribute but it seems like a good starting point since it doesn’t do much. First of all, be sure that you run with: opt -passes=attributor -attributor-disable=false This uses the new pass manager which is another discussion. Now, to the point: If you open nounwind.ll, it has a bunch of test cases and I don’t think it’s a good idea to run Attributor in all of them at first. So, break it into individual tests. First of all, note that the Attributor follows an optimistic path to attribute deduction. That is, you always start assuming that an attribute is valid until you have info that it isn’t. Seeing TEST 1 should be relatively obvious that it doesn’t have something that breaks the initial assumption, that’s why you see no change in state between calls to updateImpl(). But now we have to dig deeper: What can break our initial assumption (which is that a function does not throw) in the case of NoUnwind? You see in the topmost updateImpl() that they’re a bunch Opcodes. Those are instructions (inside our function) that can potentially break our initial assumption (e.g. call to a function that either we know it throws or at least it is not guaranteed that it doesn’t). In the updateImpl(), using checkForAllInstructions, we loop through all those instructions and call for each one the predicate CheckForNoUnwind. Note a couple of things: - TEST 1 has no such instructions whatsoever so if you put a print inside the predicate, you’ll see nothing. - You can see that the predicate returns a boolean value. If it’s true, we continue to the next instruction, otherwise we stop. If we make it through all of them, checkForAllInstructions() returns true. Otherwise false. The predicate checks if any instruction breaks our assumption (we’ll see shortly how). If it does, we immediately indicate pessimistic fixpoint. What about TEST 2 and 3 ? Those 2 functions have a call inside but if you put a print inside the predicate, you’ll see again nothing. The reason for that brings us to an important part of the Attributor and that is that “deadness” (and the relative attribute) is very important. checkForAllInstructions() will only go through instructions that are considered live. The 2 calls are not considered because another part of the Attributor (which is out of topic right now) has (somewhat) deduced that they go in an endless recursion. If you run the Attributor with these 2 functions you’ll see another important point. Specifically that the function bodies have only an unreachable instruction inside. That is, the attributor not only deduces (and provides) info through attributes but it also transforms code. In this case it changed the function bodies to unreachable. Finally, I think it’s interesting to see TEST 4: You see that it calls a function that we don’t know it doesn’t throw. This should break our assumption. And it does. Inside the topmost updateImpl() and inside the predicate, if you put a print, you’ll see the call (e.g. dbgs() << I << “\n”). We ask I.mayThrow(). Note that mayThrow() will return false in the case that we’re somehow sure that the instruction does not throw. In this case the instruction is a call, so it will return true if we’re sure that the called function does not throw. But we’re not, so we move forward. What then happens is a little bit weird but it basically AANoUnwind asks AANoUnwindCallSite for info because this instruction is a call site. Attributes ask one another and this is very important in the Attributor because one’s information is useful in another. We do it with getAAFor. Without getting into too much info, the other attribute says that it’s not assumed unwind so we indicate pessimistic fixpoint (the reality is that the order of calls between the attributes is reverse, but again, out of topic). I hope that gave you a better understanding! > I know how in [1] Johaanes explained the use of MaxObjSize and Dereferenceable in the AliasAnalysis. But I would be happy if I could come up with some even better example. As you said, that’ll probably take some time but that’s ok There are opportunities everywhere. For example, consider this: https://godbolt.org/z/HFWo_J It’s a for loop that does a load inside from %p. The load seems to be invariant, we could move it out of the loop. -licm in the cmd arguments means it invokes the Loop-Invariant Code Motion pass, which does such things. But it doesn’t move the load out. The reason for that is that consider the case where %n == 0 and %p == null. In the initial code, we would never get into the loop and we would not have a trap. While, with this transformation, we will have and thus, we just changed the initial behavior. So, the transformation is not done. However, if you put dereferenceable(4) attribute in %p, it will be done. Because now you now you can certainly dereference. So, attribute info is useful in ways we may not consider :slight_smile: > I can start with TODO at line no. 2605 // TODO: Return the number of reachable queries. I’m not familiar with it. Currently it doesn’t seem to do anything but I may miss something. I suppose what it asks is to track how many queries to this attribute have been done by outside users which should be easy. > Since the code is very large right now, I thought to refer to some of the very initial patches of attributor Maybe, I don’t know. But I assume things will have changed from then and you may get lost. I’d start by doing diagrams about how different parts of the code interact with each other (e.g. where does the Attributor start? what does it call then? how are attributes created? etc.) When starting out, these things might not be important to tackle. But they helped me. > How should I indicate to the community that I have started working towards this issue (should I comment on the issue page on github?)? I can try to work on AAReachability TODO after solving this issue.
You can write it in the Github comments. I don’t think you can / need to do something else. Kind regards, Stefanos Baziotis

Στις Δευ, 16 Μαρ 2020 στις 12:12 π.μ., ο/η Fahad Nayyar <fahad17049@iiitd.ac.in> έγραψε:

Dear Stefanos,

Thanks for such a detailed explanation!
I’ll have to study your mail and try out some things before I can ask specific questions for further discussion.

But I want to discuss this point right away:

> I’d start by doing diagrams about how different parts of the code interact with each other (e.g. where does the Attributor start? what does it call then? how are attributes created? etc.) When starting out, these things might not be important to tackle. But they helped me.

I totally agree with your point of drawing diagrams about different parts of the code. I tried this but was not able to succeed. It would be very helpful if you can tell me what is the entry point of Attributor (which method is called the very first time?)?
Also, is there any way we can debug opt command in gdb like fashion (ie. setting breakpoints, stepping through instructions one by one?)?
This would help me a lot in the initial code reading period.

Thanks and Regards
Fahad Nayyar

Thanks for such a detailed explanation!
I’ll have to study your mail and try out some things before I can ask specific questions for further discussion.

No problem, follow-up with questions if any.

I totally agree with your point of drawing diagrams about different parts of the code. I tried this but was not able to succeed. It would be very helpful if you can tell me what is the entry point of Attributor (which method is called the very first time?)? It’s runAttributorOnFunctions. I’m not sure it’s good to start seeing the whole picture right now, but in any case, you can follow that if at any point you want.
Also, is there any way we can debug opt command in gdb like fashion (ie. setting breakpoints, stepping through instructions one by one?)? It depends on how you built LLVM. If you built it with -DCMAKE_BUILD_TYPE=Release, you can’t. However note that if you built it in Release with asserts on, i.e. -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_ASSERTIONS=On, you’ll have the -debug option in opt, which can be useful at times. To be able to have debug info, you have to build it with RelWithDebInfo or Debug (in CMAKE_BUILD_TYPE, check: https://llvm.org/docs/CMake.html). Although in the former, even if you enable assertions, for some reason you don’t have -debug last time I checked. Note that in both of these settings, the binary size (and the compilation time) grow a lot (i.e. several tens of gigabytes in Debug IIRC). Best, Stefanos Baziotis

Στις Δευ, 16 Μαρ 2020 στις 5:52 π.μ., ο/η Fahad Nayyar <fahad17049@iiitd.ac.in> έγραψε:

1) Apologies for being late to the discussion.
2) I will respond to multiple mails in this thread.

Dear Stefanos,

Thanks for such a detailed explanation!
I'll have to study your mail and try out some things before I can ask
specific questions for further discussion.

But I want to discuss this point right away:

*> I'd start by doing diagrams about how different parts of the code
interact with each other (e.g. where does the Attributor start? what does
it call then? how are attributes created? etc.) When starting out, these
things might not be important to tackle. But they helped me.*

I totally agree with your point of drawing diagrams about different parts
of the code. I tried this but was not able to succeed. It would be very
helpful if you can tell me what is the entry point of Attributor (which
method is called the very first time?)?

As Stefanos noted, runAttributorOnFunctions is the "entry point". From
there we go to Attributor::run, which will then call
`AbstractAttribute::update` until a fixpoint was found or a timeout
reached.

Also, is there any way we can debug opt command in gdb like fashion (ie.
setting breakpoints, stepping through instructions one by one?)?
This would help me a lot in the initial code reading period.

I recommend to run opt with -debug-only=attributor and look at the
output for a short code example. Not all abstract attributes print much
about their internal deduction process but you see the state before and
after an update at least.

Cheers,
  Johannes

Dear Stefanos,

Thanks for such a quick response! And thanks for answering my questions!

> Starting off, understanding the theory of data-flow analysis can help.

I know about some standard fix-point lattice-based data flow analysis like
reaching definitions, live variable analysis, etc. I have done a
course on “Program
analysis” at my college.

> The deduction of these attributes is inter-connected, which is the whole
point of the Attributor.

Thanks for explaining this part with the example!

> I'd suggest that you try to run the Attributor and follow a specific
attribute's updates and see what it tries to deduce. That is, see its
updateImpl().

Thanks for suggesting this! I will try to do this and get back to you.

> At this point, LLVM is focused on heavy inlining, which while very
useful, you'll lose a lot of the interprocedural information.

I see. It would be great if we can come up with some specific examples
where using these deduced attributes can improve existing inter and intra
procedural optimization passes. I am very interested to work towards
exploring this potential of Attributor. So I would try to include such
examples in my GSOC proposal.

The most benefit comes often from liveness and we are now improving the
usage of the other attributes during liveness deduction. One example
that is part of the value simplification improvements (see below) would
be the following:

static void foo(int *A) {
  if (A == null)
    abort();
  return *A;
}
int bar(int *A) {
  *A = 1;
  return foo(A);
}

Since we know `A` is not null at the call site we know the call to abort
is dead.

> Liveness is certainly something that we're currently trying to improve
and I don't think we'll ever stop.

It would be great if you can share some of the ongoing issues or discussion
regarding improving Liveness information deduction using Attributor.

We are working on using undefined behavior (UB) to improve liveness. We
are also working to improve value simplification (partially for the same
reason). The latter has an old version online which I will replace with
smaller changes very soon (D68934). The former has quite some discussion
here D71974.

I think the AAReachability TODO is being worked on but #179 not, as far
as I know. Would you be interested in taking this one? If so, make sure
to split it in multiple smaller patches, starting with one for the
LangRef.doc and the Attributor.

FIWI, I think we want the attribute to mean 1) below. I note this
because 2) is "the opposite" of dereferenceable.
  1) the underlying object is at most this large, where the pointer
     points to doesn't matter.
  2) the underlying object has at most X more dereferenceable bytes from
     this point forward.
I think we want 1) and later the opposite of 1) as well.

Does this make sense?

Cheers,
  Johannes

Hi Johannes,

Thanks for your comments!

> I think the AAReachability TODO is being worked on but #179 not, as far as I know. Would you be interested in taking this one? If so, make sure to split it in multiple smaller patches, starting with one for the LangRef.doc and the Attributor.

Sure!. I can take this up. I’ll put up the patches asap. I have a doubt about #task1 of #179 “Write a short RFC for a the attribute and send it to llvm-dev”. What kind of description of the attribute should I put there? I was thinking about the meaning of the attribute and its purpose. Please clarify.

> FIWI, I think we want the attribute to mean 1) below. I note this
because 2) is “the opposite” of dereferenceable.
1) the underlying object is at most this large, where the pointer
points to doesn’t matter.
2) the underlying object has at most X more dereferenceable bytes from
this point forward.
I think we want 1) and later the opposite of 1) as well.
Does this make sense?

Yes. I understood this. Just for clarification the opposite of 1) will be “the underlying object is at least this large”?

Thanks and regards.
Fahad Nayyar

Hi Johannes,

>
> Thanks for your comments!
>
> > I think the AAReachability TODO is being worked on but #179 not, as far as I know. Would you be interested in taking this one? If so, make sure to split it in multiple smaller patches, starting with one for the LangRef.doc and the Attributor.
>
> Sure!. I can take this up. I'll put up the patches asap. I have a
> doubt about #task1 of #179 "Write a short RFC for a the attribute and
> send it to llvm-dev". What kind of description of the attribute should
> I put there? I was thinking about the meaning of the attribute and its
> purpose. Please clarify.

Yes. Feel free to share a draft with me. If you want I can also write
the RFC but it might take longer. My suggestion that you write a short
motivation for the attribute and the intended semantics and share that
on this thread. We go over it and send it out as an RFC after. You
should at the same time write/port the LangRef patch so we can point
people there.

> > FIWI, I think we want the attribute to mean 1) below. I note this
> because 2) is "the opposite" of dereferenceable.
> 1) the underlying object is at most this large, where the pointer
> points to doesn't matter.
> 2) the underlying object has at most X more dereferenceable bytes from
> this point forward.
> I think we want 1) and later the opposite of 1) as well.
> Does this make sense?
>
> Yes. I understood this. Just for clarification the opposite of 1) will be "the underlying object is at least this large"?

Yes. Which we for now can approximate with `dereferenceable` as it says,
there are at least that many bytes accessible from the current pointer.

> Thanks and regards.
> Fahad Nayyar
>
> > I can see that Johanned have put up some issues for GSOC aspirants. I think
> > that [2] <https://github.com/llvm/llvm-project/issues/179> ([Attributor]
> > Cleanup and upstream `Attribute::MaxObjectSize`) will be a very good issue
> > for me, It seems doable and I can get familiar with the whole process of
> > writing a patch for an issue. How should I indicate to the community that I
> > have started working towards this issue (should I comment on the issue page
> > on github?)? I can try to work on AAReachability TODO after solving this
> > issue.
>
> I think the AAReachability TODO is being worked on but #179 not, as far
> as I know. Would you be interested in taking this one? If so, make sure
> to split it in multiple smaller patches, starting with one for the
> LangRef.doc and the Attributor.
>
> FIWI, I think we want the attribute to mean 1) below. I note this
> because 2) is "the opposite" of dereferenceable.
> 1) the underlying object is at most this large, where the pointer
> points to doesn't matter.
> 2) the underlying object has at most X more dereferenceable bytes from