This document contains:
- our guidelines for bug reports
- general contribution guidelines
- a checklist for pull requests
- a developer guide that explains the development environment, project structure, and test suite
How to report bugs¶
When reporting a bug, first search our issues to avoid duplicates. In your bug report, please describe what you expected gcovr to do, and what it actually did. Also try to include the following details:
- how you invoked gcovr, i.e. the exact flags and from which directory
- your project layout
- your gcovr version
- your compiler version
- your operating system
- and any other relevant details.
Ideally, you can provide a short script and the smallest possible source file to reproduce the problem.
How to help¶
There are many ways how you can help:
- assist other users with their problems
- share your perspective as a gcovr user in discussions
- test proposed changes in your real-world projects
- improve our documentation
- submit pull requests with bug fixes and enhancements
How to submit a Pull Request¶
Thank you for helping with gcovr development! Please follow this checklist for your pull request:
Is this a good approach? Fixing open issues is always welcome! If you want to implement an enhancement, please discuss it first as a GitHub issue.
Does it work? Please run the tests locally:
(see also: Test suite)
In any case, the tests will run automatically when you open the pull request. But please prevent unnecessary build failures and run the tests yourself first. If you cannot run the tests locally, you can activate GitHub or Appveyor for your fork, or run the tests with Docker.
If you add new features, please try to add a test case.
Does it conform to the style guide? The source code should conform to the PEP 8 standard. Please check your code:
make lint # or: python3 -m flake8 doc gcovr --ignore E501,W503
make qawill run the linter, run the tests, and check that the docs can be built.
Add yourself as an author. If this is your first contribution to gcovr, please add yourself to the
One change at a time. Please keep your commits and your whole pull request fairly small, so that the changes are easy to review. Each commit should only contain one kind of change, e.g. refactoring or new functionality.
Why is this change necessary? When you open the PR, please explain why we need this change and what your PR does. If this PR fixes an open issue, reference that issue in the pull request description.
Once you submit the PR, it will be automatically tested on Windows and Linux, and code coverage will be collected. Your code will be reviewed. This can take a week. Please fix any issues that are discovered during this process. Feel free to force-push your updates to the pull request branch.
If you need assistance for your pull request, you can
- chat in our Gitter room
- discuss your problem in an issue
- open an unfinished pull request as a work in progress (WIP), and explain what you’ve like to get reviewed
How to set up a development environment¶
For working on gcovr, you will need a supported version of Python 3, and GCC version 5. Other GCC versions are supported by gcovr, but will cause spurious test failures.
(Optional) Fork the project on GitHub.
Clone the git repository.
(Optional) Set up a virtualenv (e.g. with
python3 -m venv my-venv)
Install gcovr in development mode, and install the test requirements:
make setup-dev # install all test + doc dependencies # or: pip install -e . pip install -r requirements.txt
You can then run gcovr as
python3 -m gcovr.
Run the tests to verify that everything works (see Test suite).
(Optional) Install documentation requirements:
# would be already done by `make setup-dev` pip install -r doc/requirements.txt
doc/README.txtfor details on working with the documentation.
(Optional) Activate GitHub and Appveyor for your forked GitHub repository, so that the cross-platform compatibility tests get run whenever you push your work to your repository. These tests will also be run when you open a pull request to the main gcovr repository.
Tip: If you have problems getting everything set up, consider looking at these files:
- for Linux:
- for Windows:
On Windows, you will need to install a GCC toolchain
as the tests expect a Unix-like environment.
You can use MinGW-W64 or MinGW.
To run the tests,
please make sure that the
cmake from your MinGW distribution
are in the system
If setting up a local toolchain is too complicated, you can also run the tests in a Docker container (see Test suite).
||the gcovr source code (Python module)|
||command line interface + top-level behaviour|
||HTML report templates|
||unit tests + integration test corpus|
||Python package configuration|
||user guide + website|
||runnable examples for the user guide|
The program entrypoint and command line interface is in
The coverage data is parsed in the
The HTML, XML, text, and summary reports
gcovr.html_generator and respective modules.
The QA process (
make qa) consists of multiple parts:
- unit tests in
- integration tests in
- documentation examples in
- unit tests in
documentation build (
The tests are in the
You can run the tests with
make test or
python3 -m pytest gcovr.
There are unit tests for some parts of gcovr,
and a comprehensive corpus of example projects
that are executed as the
test_gcovr.py integration test.
gcovr/tests/* directory is one such example project.
Structure of integration tests¶
Each project in the corpus
Makefile and a
gcovr/tests/sometest/ reference/ Makefile README example.cpp
The Makefile controls how the project is built, and how gcovr should be invoked. The reference directory contains baseline files against which the gcovr output is compared. Tests can be executed even without baseline files.
Each Makefile contains the following targets:
all:builds the example project. Can be shared between gcovr invocations.
run:lists available targets which must be a subset of the available output formats.
clean:remove any generated files after all tests of the scenario have finished.
- output formats (txt, html, json, sonarqube, …): invoke gcovr to produce output files of the correct format. The test runner automatically finds the generated files (if any) and compares them to the baseline files in the reference directory. All formats are optional, but using at least JSON is recommended.
clean-each:if provided, will be invoked by the test runner after testing each format.
Run and filter tests¶
To run all tests, use
make test or
The tests currently assume that you are using GCC 5
and have set up a development environment.
You can run the tests with additional options by setting
Run all tests after each change is a bit slow, therefore you can limit the tests
to a specific test file, example project, or output format.
# run only XML tests make test TEST_OPTS="-k 'xml'" # run the simple1 tests make test TEST_OPTS="-k 'simple1'" # run the simple1 tests only for XML make test TEST_OPTS="-k 'xml and simple1'"
To see which tests would be run, add the
#see which tests would be run make test TEST_OPTS="--collect-only"
Sometimes during development you need to create reference files for new test
or update the current reference files. To do this you have to
By default generated output files are automatically removed after test run.
To skip this process you can add
--skip_clean option the
# run tests and generate references for simple1 example make test TEST_OPTS="-k 'simple1' --generate_reference" # run tests and update xml references for simple1 example make test TEST_OPTS="-k 'xml and simple1' --update_reference" # run only XML tests and do not remove generated files make test TEST_OPTS="-k 'xml' --skip_clean"
When the currently generated output reports differ to the reference files
you can create a ZIP archive named
diff.zip in the tests directory
Currently in gcovr it is used by AppVeyor CI to create a ZIP file
with the differences as an artifact.
# run tests and generate a ZIP archive when there were differences make test TEST_OPTS="--archive_differences"
New in version NEXT: Added test options --generate_reference, --update_reference,
--skip_clean, ‘--archive_differences’ and changed way to call tests
Run tests with Docker¶
If you can’t set up a toolchain locally, you can run the QA process via Docker. First, build the container image:
make docker-qa-build # or: docker build --tag gcovr-qa --file admin/Dockerfile.qa .
Then, run the container, which executes
make qa within the container:
make docker-qa # or: docker run --rm -v `pwd`:/gcovr gcovr-qa
Become a gcovr developer¶
After you’ve contributed a bit (whether with discussions, documentation, or code), consider becoming a gcovr developer. As a developer, you can:
- manage issues and pull requests (label and close them)
- review pull requests (a developer must approve each PR before it can be merged)
- participate in votes
Just open an issue that you’re interested, and we’ll have a quick vote.