Best Code Coverage Tools for Coveralls

Find and compare the best Code Coverage tools for Coveralls in 2025

Use the comparison tool below to compare the top Code Coverage tools for Coveralls on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Go Reviews

    Go

    Golang

    Free
    Thanks to a comprehensive array of tools and APIs available from leading cloud providers, developing services in Go has never been more accessible. The language's extensive open-source libraries, combined with its powerful standard library, make it ideal for crafting swift and sophisticated command-line interfaces. Go's exceptional memory management and compatibility with multiple integrated development environments enhance its capability to drive rapid and scalable web applications. With quick compilation times and a clean syntax, along with built-in formatting and documentation tools, Go is tailored to meet the needs of both DevOps professionals and site reliability engineers. This is a deep dive into everything related to Go. Whether you are embarking on a fresh project or looking to refine your existing Go skills, there’s a structured interactive introduction that is divided into three parts. Each part offers practical exercises to reinforce your understanding, and the Playground feature allows users to write Go code directly in a browser, which is then compiled, linked, and executed on our servers instantly. This hands-on approach makes learning Go not only effective but also enjoyable.
  • 2
    grcov Reviews

    grcov

    grcov

    Free
    grcov is a tool that gathers and consolidates code coverage data from various source files. It is capable of processing .profraw and .gcda files produced by llvm/clang or gcc compilers. Additionally, grcov can handle lcov files for JavaScript coverage and JaCoCo files for Java applications. This versatile tool is compatible with operating systems including Linux, macOS, and Windows, making it widely accessible for developers across different platforms. Its functionality enhances the ability to analyze code quality and test coverage effectively.
  • 3
    kcov Reviews

    kcov

    kcov

    Free
    Kcov is a code coverage testing tool available for FreeBSD, Linux, and OSX that caters to compiled languages, Python, and Bash. Initially derived from Bcov, Kcov has developed into a more robust tool, incorporating an extensive array of features beyond those offered by its predecessor. Similar to Bcov, Kcov leverages DWARF debugging data from compiled programs, enabling the gathering of coverage metrics without the need for specific compiler flags. This functionality streamlines the process of assessing code coverage, making it more accessible for developers across various programming languages.
  • 4
    test_coverage Reviews
    A straightforward command-line utility designed to gather test coverage data from Dart VM tests, making it an essential tool for developers who require local coverage reports while working on their projects. This tool streamlines the process of analyzing test effectiveness and ensures that developers can easily monitor their code's test coverage in real-time.
  • 5
    Slather Reviews

    Slather

    Slather

    Free
    To create test coverage reports for Xcode projects and integrate them into your continuous integration (CI) system, make sure to activate the coverage feature by checking the "Gather coverage data" option while modifying the scheme settings. This setup will help you track code quality and ensure that your tests effectively cover the necessary parts of your application, streamlining your development process.
  • 6
    DeepCover Reviews

    DeepCover

    DeepCover

    Free
    Deep Cover strives to be the premier tool for Ruby code coverage, delivering enhanced accuracy for both line and branch coverage metrics. It serves as a seamless alternative to the standard Coverage library, providing a clearer picture of code execution. A line is deemed covered only when it has been fully executed, and the optional branch coverage feature identifies any branches that remain untraveled. The MRI implementation considers all methods available, including those created through constructs like define_method and class_eval. Unlike Istanbul's method, DeepCover encompasses all defined methods and blocks when reporting coverage. Although loops are not classified as branches within DeepCover, accommodating them can be easily arranged if necessary. Even once DeepCover is activated and set up, it requires only a minimal amount of code loading, with coverage tracking starting later in the process. To facilitate an easy migration for projects that have previously relied on the built-in Coverage library, DeepCover can integrate itself into existing setups, ensuring a smooth transition for developers seeking improved coverage analysis. This capability makes DeepCover not only versatile but also user-friendly for teams looking to enhance their testing frameworks.
  • 7
    CodeShip Reviews

    CodeShip

    CloudBees

    $49 per month
    Would you prefer an instant setup for all your needs, or do you value the ability to tailor your environment and workflow? CodeShip empowers developers to choose the most effective route for their needs, enhancing productivity and allowing teams to adapt over time. It offers a comprehensive suite of features, from deployment and notifications to code coverage, security scanning, and on-premise source control management, enabling seamless integration with any necessary tools, services, or cloud platforms for an ideal workflow. Our goal is not only to make CodeShip user-friendly but also to deliver prompt and comprehensive support for developers. When you encounter an issue or require assistance, having access to knowledgeable technical support without delay is crucial, and that’s a commitment we uphold at CodeShip. You can initiate your builds and deployments in under five minutes using CodeShip’s straightforward environment and intuitive interface. As your projects expand, you can gradually transition to more advanced workflows and configuration-as-code, ensuring your tools grow with your needs. This flexible approach ensures that as your requirements change, your workflow can adapt without missing a beat.
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