Code Coverage in Chromium

Coverage Dashboard: link

Table of contents:

This document is divided into two parts.

  • The first part introduces the code coverage infrastructure that continuously generates code coverage information for the whole codebase and for specific CLs in Gerrit. For the latter, refer to
  • The second part talks about how to generate code coverage locally for Clang-compiled languages like C++. Refer to android code coverage instructions for instructions for java code.

Coverage Infrastructure

coverage infra diagram

There are 3 layers in the system:

Coverage Builders

The first layer is the LUCI builders that

  • build instrumented targets,
  • run the instrumented tests,
  • merge the results into single streams,
  • upload data to cloud storage.

There are two types of builder:

CI Builder

The code coverage CI Builders periodically build all the test targets and fuzzer targets for a given platform and instrument all available source files. Then save the coverage data to a dedicated storage bucket.

CQ Builder

The code coverage CQ builders instrument only the files changed for a given CL. More information about per-cl coverage info in this doc.

Coverage Service

The second layer in the system consists of an AppEngine application that consumes the coverage data from the builders above, structures it and stores it in cloud datastore. It then serves the information to the clients below.

Coverage Clients

In the last layer we currently have two clients that consume the service:

Coverage Dashboard

The coverage dashboard front end is hosted in the same application as the service above. It shows the full-code coverage reports with links to the builds that generated them, as well as per-directory and per-component aggregation, and can be drilled down to the single line of code level of detail.

Refer to the following screenshots:

Directory View

See coverage breakdown by directories (default landing page).

coverage dashboard directory view

Component View

Use the view dropdown menu to switch between directory and component.

coverage dashboard component view

Source View

Click on a particular source file in one of the views above to see line-by-line coverage breakdown, and it's useful to identify:

  • Uncovered lines and code blocks that lack test coverage.
  • Potentially dead code. See dead code example.
  • Hot spots in your code.

coverage dashboard file view

Project View

Click on “Previous Reports” to check out the coverage history of the project.

coverage dashboard link to previous reports

List of historical coverage reports are in reverse chronological order.

coverage dashboard previous reports

Gerrit Coverage View

The other client supported at the moment is the gerrit plugin for code coverage.

gerrit coverage view

See this doc for information about the feature that allows gerrit to display code coverage information generated for a given CL by CQ bot. Or see this 15-second video tutorial.

Local Coverage Script

This documentation explains how to use Clang’s source-based coverage features in general. The coverage script automates the process described below and provides a one-stop service to generate code coverage reports locally in just one command.

This script is currently supported on Android, Linux, Mac, iOS and ChromeOS platforms.

Here is an example usage:

$ gn gen out/coverage \
    --args="use_clang_coverage=true is_component_build=false
    dcheck_always_on=true is_debug=false"
$ python tools/code_coverage/ \
    crypto_unittests url_unittests \
    -b out/coverage -o out/report \
    -c 'out/coverage/crypto_unittests' \
    -c 'out/coverage/url_unittests --gtest_filter=URLParser.PathURL' \
    -f url/ -f crypto/

The command above builds crypto_unittests and url_unittests targets and then runs them individually with their commands and arguments specified by the -c flag. For url_unittests, it only runs the test URLParser.PathURL. The coverage report is filtered to include only files and sub-directories under url/ and crypto/ directories.

Aside from automating the process, this script provides visualization features to view code coverage breakdown by directories and by components, similar to the views in the coverage dashboard above.


This section presents the workflow of generating code coverage reports using two unit test targets in Chromium repo as an example: crypto_unittests and url_unittests, and the following diagram shows a step-by-step overview of the process.

code coverage generation workflow

Step 0 Download Tooling

Generating code coverage reports requires llvm-profdata and llvm-cov tools. You can get them by adding "checkout_clang_coverage_tools": True, to custom_vars in the .gclient config and run gclient runhooks. You can also download the tools manually (tools link)

Step 1 Build

In Chromium, to compile code with coverage enabled, one needs to add use_clang_coverage=true, is_component_build=false and is_debug=false GN flags to the file in the build output directory. Under the hood, they ensure -fprofile-instr-generate and -fcoverage-mapping flags are passed to the compiler.

$ gn gen out/coverage \
    --args='use_clang_coverage=true is_component_build=false is_debug=false'
$ gclient runhooks
$ autoninja -C out/coverage crypto_unittests url_unittests

Step 2 Create Raw Profiles

The next step is to run the instrumented binaries. When the program exits, it writes a raw profile for each process. Because Chromium runs tests in multiple processes, the number of processes spawned can be as many as a few hundred, resulting in the generation of a few hundred gigabytes’ raw profiles. To limit the number of raw profiles, %Nm pattern in LLVM_PROFILE_FILE environment variable is used to run tests in multi-process mode, where N is the number of raw profiles. With N = 4, the total size of the raw profiles are limited to a few gigabytes. (If working on Android, the .profraw files will be located in ./out/coverage/coverage by default.)

Additionally, we also recommend enabling the continuous mode by adding the %c pattern to LLVM_PROFILE_FILE. The continuous mode updates counters in real time instead of flushing to disk at process exit. This recovers coverage data from tests that exit abnormally (e.g. death tests). Furthermore, the continuous mode is required to recover coverage data for tests that run in sandboxed processes. For more information, see

$ export LLVM_PROFILE_FILE="out/report/crypto_unittests.%4m%c.profraw"
$ ./out/coverage/crypto_unittests
$ ls out/report/

Step 3 Create Indexed Profile

Raw profiles must be indexed before generating code coverage reports, and this is done using the merge command of llvm-profdata tool, which merges multiple raw profiles (.profraw) and indexes them to create a single profile (.profdata).

At this point, all the raw profiles can be thrown away because their information is already contained in the indexed profile.

$ llvm-profdata merge -o out/report/coverage.profdata \
$ ls out/report/coverage.profdata

Step 4 Create Coverage Reports

Finally, llvm-cov is used to render code coverage reports. There are different report generation modes, and all of them require the following as input:

  • Indexed profile
  • All built target binaries
  • All exercised source files

For example, the following command can be used to generate per-file line-by-line code coverage report:

$ llvm-cov show -output-dir=out/report -format=html \
    -instr-profile=out/report/coverage.profdata \
    -compilation-dir=out/coverage \
    -object=out/coverage/url_unittests \

If creating a report for Android, the -object arg would be the lib.unstripped file, ie out/coverage/lib.unstripped/

For more information on how to use llvm-cov, please refer to the guide.


Reporting problems

For any breakage report and feature requests, please file a bug.

Mailing list

For questions and general discussions, please join code-coverage group.


Can I use is_component_build=true for code coverage build?

Yes, code coverage instrumentation works with both component and non-component builds. Component build is usually faster to compile, but can be up to several times slower to run with code coverage instrumentation. For more information, see

I am getting some warnings while using the script, is that fine?

Usually this is not a critical issue, but in general we tend not to have any warnings. Please check the list of known issues, and if there is a similar bug, leave a comment with the command you run, the output you get, and Chromium revision you use. Otherwise, please file a bug providing the same information.

How do crashes affect code coverage?

If a crash of any type occurs (e.g. Segmentation Fault or ASan error), the crashing process might not dump coverage information necessary to generate code coverage report. For single-process applications (e.g. fuzz targets), that means no coverage might be reported at all. For multi-process applications, the report might be incomplete. It is important to fix the crash first. If this is happening only in the coverage instrumented build, please file a bug.

How do assertions affect code coverage?

If a crash is caused by CHECK or DCHECK, the coverage dump will still be written on the disk ( However, if a crashing process calls the standard assert directly or through a custom wrapper, the dump will not be written (see How do crashes affect code coverage?).

Is it possible to obtain code coverage from a full Chromium build?

Yes, with some important caveats. It is possible to build chrome target with code coverage instrumentation enabled. However, there are some inconveniences involved:

  • Linking may take a while, especially if you use a non-component build.
  • The binary is huge (2-4GB).
  • The browser may be noticeably slow and laggy.

For more information, please see

Why do we see significantly different coverage reported on different revisions?

There can be two possible scenarios:

  • It can be a one time flakiness due to a broken build or failing tests.
  • It can be caused by extension of the test suite used for generating code coverage reports. When we add new tests to the suite, the aggregate coverage reported usually grows after that.

How can I improve coverage dashboard?

The code for the service and dashboard currently lives along with findit at this location because of significant shared logic.

The code used by the bots that generate the coverage data lives (among other places) in the code coverage recipe module.

Why is coverage for X not reported or unreasonably low, even though there is a test for X?

There are several reasons why coverage reports can be incomplete or incorrect:

  • A particular test is not used for code coverage report generation. Please file a bug.
  • A test may have a build failure or a runtime crash. Please check the build for that particular report (rightmost column on the coverage dashboard). If there is any failure, please upload a CL with the fix. If you can't fix it, feel free to file a bug.
  • A particular test may not be available on a particular platform. As of now, only reports generated on Linux and CrOS are available on the coverage dashboard.

Is coverage reported for the code executed inside the sandbox?