This tutorial will guide you through the process of making a change to LLVM, and contributing it back to the LLVM project. We’ll be making a change to Clang, but the steps for other parts of LLVM are the same. Even though the change we’ll be making is simple, we’re going to cover steps like building LLVM, running the tests, and code review. This is good practice, and you’ll be prepared for making larger changes.

We’ll assume you:

  • know how to use an editor,

  • have basic C++ knowledge,

  • know how to install software on your system,

  • are comfortable with the command line,

  • have basic knowledge of git.

The change we’re making

Clang has a warning for infinite recursion:

$ echo "void foo() { foo(); }" > ~/
$ clang -c -Wall ~/ warning: all paths through this function will call itself [-Winfinite-recursion]

This is clear enough, but not exactly catchy. Let’s improve the wording a little: warning: to understand recursion, you must first understand recursion [-Winfinite-recursion]


We’re going to need some tools:

  • git: to check out the LLVM source code,

  • a C++ compiler: to compile LLVM source code. You’ll want a recent version <host_cpp_toolchain> of Clang, GCC, or Visual Studio.

  • CMake: used to configure how LLVM should be built on your system,

  • ninja: runs the C++ compiler to (re)build specific parts of LLVM,

  • python: to run the LLVM tests.

As an example, on Ubuntu:

$ sudo apt-get install git clang cmake ninja-build python

Building LLVM


The source code is stored on Github in one large repository (“the monorepo”).

It may take a while to download!

$ git clone

This will create a directory “llvm-project” with all of the source code. (Checking out anonymously is OK - pushing commits uses a different mechanism, as we’ll see later.)

Configure your workspace

Before we can build the code, we must configure exactly how to build it by running CMake. CMake combines information from three sources:

  • explicit choices you make (is this a debug build?)

  • settings detected from your system (where are libraries installed?)

  • project structure (which files are part of ‘clang’?)

First, create a directory to build in. Usually, this is llvm-project/build.

$ mkdir llvm-project/build
$ cd llvm-project/build

Now, run CMake:

$ cmake -G Ninja ../llvm -DCMAKE_BUILD_TYPE=Release -DLLVM_ENABLE_PROJECTS=clang

If all goes well, you’ll see a lot of “performing test” lines, and finally:

Configuring done
Generating done
Build files have been written to: /path/llvm-project/build

And you should see a file in the current directory.

Let’s break down that last command a little:

  • -G Ninja: Tells CMake that we’re going to use ninja to build, and to create the file.

  • ../llvm: this is the path to the source of the “main” LLVM project

  • The two -D flags set CMake variables, which override CMake/project defaults:

    • CMAKE_BUILD_TYPE=Release: build in optimized mode, which is (surprisingly) the fastest option.

      If you want to run under a debugger, you should use the default Debug (which is totally unoptimized, and will lead to >10x slower test runs) or RelWithDebInfo which is a halfway point.

      Assertions are not enabled in Release builds by default. You can enable them using LLVM_ENABLE_ASSERTIONS=ON.

    • LLVM_ENABLE_PROJECTS=clang: this lists the LLVM subprojects you are interested in building, in addition to LLVM itself. Multiple projects can be listed, separated by semicolons, such as clang;lldb. In this example, we’ll be making a change to Clang, so we only add clang.

Finally, create a symlink (or copy) of llvm-project/build/compile-commands.json into llvm-project/:

$ ln -s build/compile_commands.json ../

(This isn’t strictly necessary for building and testing, but allows tools like clang-tidy, clang-query, and clangd to work in your source tree).

Build and test

Finally, we can build the code! It’s important to do this first, to ensure we’re in a good state before making changes. But what to build? In ninja, you specify a target. If we just want to build the clang binary, our target name is “clang” and we run:

$ ninja clang

The first time we build will be very slow - Clang + LLVM is a lot of code. But incremental builds are fast: ninja will only rebuild the parts that have changed. When it finally finishes you should have a working clang binary. Try running:

$ bin/clang --version

There’s also a target for building and running all the clang tests:

$ ninja check-clang

This is a common pattern in LLVM: check-llvm is all the checks for the core of LLVM, other projects have targets like check-lldb, check-flang and so on.

Making changes

The Change

We need to find the file containing the error message.

$ git grep "all paths through this function" ..
../clang/include/clang/Basic/  "all paths through this function will call itself">,

The string that appears in is the one that is printed by Clang. *.td files define tables - in this case it’s a list of warnings and errors clang can emit and their messages. Let’s update the message in your favorite editor:

$ vi ../clang/include/clang/Basic/

Find the message (it should be under warn_infinite_recursive_function). Change the message to “in order to understand recursion, you must first understand recursion”.

Test again

To verify our change, we can build clang and manually check that it works.

$ ninja clang
$ bin/clang -c -Wall ~/ warning: in order to understand recursion, you must first understand recursion [-Winfinite-recursion]

We should also run the tests to make sure we didn’t break something.

$ ninja check-clang

Notice that it is much faster to build this time, but the tests take just as long to run. Ninja doesn’t know which tests might be affected, so it runs them all.

Failing Tests (1):
    Clang :: SemaCXX/warn-infinite-recursion.cpp

Well, that makes sense… and the test output suggests it’s looking for the old string “call itself” and finding our new message instead. Note that more tests may fail in a similar way as new tests are added over time.

Let’s fix it by updating the expectation in the test.

$ vi ../clang/test/SemaCXX/warn-infinite-recursion.cpp

Everywhere we see // expected-warning{{call itself}} (or something similar from the original warning text), let’s replace it with // expected-warning{{to understand recursion}}.

Now we could run all the tests again, but this is a slow way to iterate on a change! Instead, let’s find a way to re-run just the specific test. There are two main types of tests in LLVM:

  • lit tests (e.g. SemaCXX/warn-infinite-recursion.cpp).

These are fancy shell scripts that run command-line tools and verify the output. They live in files like clang/**test**/FixIt/dereference-addressof.c. Re-run like this:

$ bin/llvm-lit -v ../clang/test/SemaCXX/warn-infinite-recursion.cpp
  • unit tests (e.g. ToolingTests/ReplacementTest.CanDeleteAllText)

These are C++ programs that call LLVM functions and verify the results. They live in suites like ToolingTests. Re-run like this:

$ ninja ToolingTests && tools/clang/unittests/Tooling/ToolingTests --gtest_filter=ReplacementTest.CanDeleteAllText

Commit locally

We’ll save the change to a local git branch. This lets us work on other things while the change is being reviewed. Changes should have a title and description, to explain to reviewers and future readers of the code why the change was made.

For now, we’ll only add a title.

$ git checkout -b myfirstpatch
$ git commit -am "[clang][Diagnostic] Clarify -Winfinite-recursion message"

Now we’re ready to send this change out into the world!

The [clang] and [Diagnostic] prefixes are what we call tags. This loose convention tells readers of the git log what areas a change is modifying. If you don’t know the tags for the modules you’ve changed, you can look at the commit history for those areas of the repository.

$ git log --oneline ../clang/

Or using GitHub, for example

Tagging is imprecise, so don’t worry if you are not sure what to put. Reviewers will suggest some if they think they are needed.

Code review

Uploading a change for review

LLVM code reviews happen through pull-request on GitHub, see the GitHub documentation for how to open a pull-request on GitHub.

Finding a reviewer

Changes can be reviewed by anyone in the LLVM community. For larger and more complicated changes, it’s important that the reviewer has experience with the area of LLVM and knows the design goals well. The author of a change will often assign a specific reviewer. git blame and git log can be useful to find previous authors who can review.

Our GitHub bot will also tag and notify various “teams” around LLVM. The team members contribute and review code for those specific areas regularly, so one of them will review your change if you don’t pick anyone specific.

Review process

When you open a pull-request, some automation will add a comment and notify different members of the sub-projects depending on the parts you have changed.

Within a few days, someone should start the review. They may add themselves as a reviewer, or simply start leaving comments. You’ll get another email any time the review is updated. For more detail see the Code Review Poilicy.


The reviewer can leave comments on the change, and you can reply. Some comments are attached to specific lines, and appear interleaved with the code. You can reply to these. Perhaps to clarify what was asked or to tell the reviewer that you have done what was asked.

Updating your change

If you make changes in response to a reviewer’s comments, simply update your branch with more commits and push to your GitHub fork of llvm-project. It is best if you answer comments from the reviewer directly instead of expecting them to read through all the changes again.

For example you might comment “I have done this.” or “I was able to this part but have a question about…”.

Review expectations

In order to make LLVM a long-term sustainable effort, code needs to be maintainable and well tested. Code reviews help to achieve that goal. Especially for new contributors, that often means many rounds of reviews and push-back on design decisions that do not fit well within the overall architecture of the project.

For your first patches, this means:

  • be kind, and expect reviewers to be kind in return - LLVM has a Code of Conduct that everyone should be following;

  • be patient - understanding how a new feature fits into the architecture of the project is often a time consuming effort, and people have to juggle this with other responsibilities in their lives; ping the review once a week when there is no response;

  • if you can’t agree, generally the best way is to do what the reviewer asks; we optimize for readability of the code, which the reviewer is in a better position to judge; if this feels like it’s not the right option, you can ask them in a comment or add another reviewer to get a second opinion.

Accepting a pull request

When the reviewer is happy with the change, they will Approve the pull request. They may leave some more minor comments that you should address before it is merged, but at this point the review is complete. It’s time to get it merged!

Commit access

Commit by proxy

As this is your first change, you won’t have access to merge it yourself yet. The reviewer does not know this, so you need to tell them! Leave a comment on the review like:

Thanks @<username of reviewer>. I don’t have commit access, can you merge this PR for me?

The pull-request will be closed and you will be notified by GitHub.

Getting commit access

Once you’ve contributed a handful of patches to LLVM, start to think about getting commit access yourself. It’s probably a good idea if:

  • you’ve landed 3-5 patches of larger scope than “fix a typo”

  • you’d be willing to review changes that are closely related to yours

  • you’d like to keep contributing to LLVM.

The process is described in the developer policy document.

With great power

Actually, this would be a great time to read the rest of the developer policy too.

Issues After Landing Your PR

Once your change is submitted it will be picked up by automated build bots that will build and test your patch in a variety of configurations.

The “console” view at displays results for specific commits. If you want to follow how your change is affecting the build bots, this should be the first place to look.

The columns are build configurations and the rows are individual commits. Along the rows are colored bubbles. The color of the bubble represents the build’s status. Green is passing, red has failed and yellow is a build in progress.

A red build may have already been failing before your change was committed. This means you didn’t break the build but you should check that you did not make it any worse by adding new problems.


Only recent changes are shown in the console view. If your change is not there, rely on PR comments and build bot emails to notify you of any problems.

If there is a problem in a build that includes your changes, you may receive a report by email or as a comment on your PR. Please check whether the problem has been caused by your changes specifically. As builds contain changes from many authors and sometimes fail due to unrelated infrastructure problems.

To see the details of a build, click the bubble in the console view, or the link provided in the problem report. You will be able to view and download logs for each stage of that build.

If you need help understanding the problem, or have any other questions, you can ask them as a comment on your PR, or on Discord.

If you do not receive any reports of problems, no action is required from you. Your changes are working as expected, well done!


If your change has caused a problem, it should be reverted as soon as possible. This is a normal part of LLVM development, that every committer (no matter how experienced) goes through.

If you are in any doubt whether your change can be fixed quickly, revert it. Then you have plenty of time to investigate and produce a solid fix.

Someone else may revert your change for you, or you can create a revert pull request using the GitHub interface. Add your original reviewers to this new pull request if possible.


Now you should have an understanding of the life cycle of a contribution to the LLVM Project.

If some details are still unclear, do not worry. The LLVM Project’s process does differ from what you may be used to elsewhere on GitHub. Within the project the expectations of different sub-projects may vary too.

So whatever you are contributing to, know that we are not expecting perfection. Please ask questions whenever you are unsure, and expect that if you have missed something, someone will politely point it out and help you address it.