Compare the Top Code Coverage Tools for Linux as of April 2025

This a list of Code Coverage tools for Linux. Use the filters on the left to add additional filters for products that have integrations with Linux. View the products that work with Linux in the table below.

What are Code Coverage Tools for Linux?

Code coverage tools are software utilities designed to analyze the source code of an application and report on the level of code that is tested by automated tests. They usually measure the percentage of lines, blocks, or branches of code that have been executed in a test suite. Many popular programming languages have their own code coverage tools available for developers to use. Compare and read user reviews of the best Code Coverage tools for Linux currently available using the table below. This list is updated regularly.

  • 1
    Parasoft

    Parasoft

    Parasoft

    Parasoft helps organizations continuously deliver high-quality software with its AI-powered software testing platform and automated test solutions. Supporting embedded and enterprise markets, Parasoft’s proven technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.
    Starting Price: $125/user/mo
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  • 2
    Tarpaulin

    Tarpaulin

    Tarpaulin

    Tarpaulin is a code coverage reporting tool for the cargo build system, named for a waterproof cloth used to cover cargo on a ship. Currently, tarpaulin provides working line coverage and while fairly reliable may still contain minor inaccuracies in the results. A lot of work has been done to get it working on a wide range of projects, but often unique combinations of packages and build features can cause issues so please report anything you find that's wrong. Also, check out our roadmap for planned features. On Linux Tarpaulin's default tracing backend is still Ptrace and will only work on x86 and x64 processors. This can be changed to the llvm coverage instrumentation with engine llvm, for Mac and Windows this is the default collection method. It can also be run in Docker, which is useful for when you don't use Linux but want to run it locally.
    Starting Price: Free
  • 3
    kcov

    kcov

    kcov

    Kcov is a FreeBSD/Linux/OSX code coverage tester for compiled languages, Python and Bash. Kcov was originally a fork of Bcov, but has since evolved to support a large feature set in addition to that of Bcov. Kcov, like Bcov, uses DWARF debugging information for compiled programs to make it possible to collect coverage information without special compiler switches.
    Starting Price: Free
  • 4
    pytest-cov
    This plugin produces coverage reports. Compared to just using coverage run this plugin does some extras. Subprocess support, so you can fork or run stuff in a subprocess and will get covered without any fuss. Xdist support, so you can use all of pytest-xdist’s features and still get coverage. Consistent pytest behavior. All features offered by the coverage package should work, either through pytest-cov’s command line options or through coverage’s config file. Under certain scenarios, a stray .pth file may be left around in site packages. The data file is erased at the beginning of testing to ensure clean data for each test run. If you need to combine the coverage of several test runs you can use the --cov-append option to append this coverage data to coverage data from previous test runs. The data file is left at the end of testing so that it is possible to use normal coverage tools to examine it.
    Starting Price: Free
  • 5
    Coverage.py

    Coverage.py

    Coverage.py

    Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.
    Starting Price: Free
  • 6
    Coveralls

    Coveralls

    Coveralls

    We help you deliver code confidently by showing which parts of your code aren’t covered by your test suite. Free for open-source repositories. Pro accounts for private repositories. Instant sign-up through GitHub, Bitbucket, and Gitlab. Maintaining a well-tested codebase is mission-critical. Figuring out where your tests are lacking can be painful. You're already running your tests on a continuous integration server, so shouldn't it be doing the heavy lifting? Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. If you're just running your code coverage locally, you won't be able to see changes and trends that occur during your entire development cycle. Coveralls lets you inspect every detail of your coverage with unlimited history. Coveralls takes the pain out of tracking your code coverage. Know where you stand with your untested code. Develop with confidence that your code is covered.
    Starting Price: $10 per month
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