Best Code Coverage Tools for Codecov
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Compare the Top Code Coverage Tools that integrate with Codecov as of April 2026
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This a list of Code Coverage tools that integrate with Codecov. Use the filters on the left to add additional filters for products that have integrations with Codecov. View the products that work with Codecov in the table below.
What are Code Coverage Tools for Codecov?
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 Codecov currently available using the table below. This list is updated regularly.
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1
Xcode
Apple
Xcode is Apple’s integrated development environment for building, testing, and distributing apps across Apple platforms. It provides powerful tools for coding, debugging, profiling, and simulation in one unified workspace. Predictive code completion and coding intelligence help developers write cleaner, faster code. Xcode supports advanced debugging and performance analysis to identify issues early. Built-in simulators allow developers to prototype apps across Apple devices without physical hardware. Testing frameworks ensure apps meet quality and performance standards. Xcode streamlines the entire app development lifecycle from idea to deployment.Starting Price: Free -
2
Go
Golang
With a strong ecosystem of tools and APIs on major cloud providers, it is easier than ever to build services with Go. With popular open source packages and a robust standard library, use Go to create fast and elegant CLIs. With enhanced memory performance and support for several IDEs, Go powers fast and scalable web applications. With fast build times, lean syntax, an automatic formatter and doc generator, Go is built to support both DevOps and SRE. Everything there is to know about Go. Get started on a new project or brush up for your existing Go code. An interactive introduction to Go in three sections. Each section concludes with a few exercises so you can practice what you've learned. The Playground allows anyone with a web browser to write Go code that we immediately compile, link, and run on our servers.Starting Price: Free -
3
PHPUnit
PHPUnit
PHPUnit requires the dom and json extensions, which are normally enabled by default. PHPUnit also requires the pcre, reflection, and spl extensions. These standard extensions are enabled by default and cannot be disabled without patching PHP’s build system and/or C sources. The code coverage report feature requires the Xdebug (2.7.0 or later) and tokenizer extensions. Generating XML reports requires the xmlwriter extension. Unit Tests are primarily written as a good practice to help developers identify and fix bugs, to refactor code and to serve as documentation for a unit of software under test. To achieve these benefits, unit tests ideally should cover all the possible paths in a program. One unit test usually covers one specific path in one function or method. However a test method is not necessarily an encapsulated, independent entity. Often there are implicit dependencies between test methods, hidden in the implementation scenario of a test.Starting Price: Free -
4
Devel::Cover
metacpan
This module provides code coverage metrics for Perl. Code coverage metrics describe how thoroughly tests exercise code. By using Devel::Cover you can discover areas of code not exercised by your tests and determine which tests to create to increase coverage. Code coverage can be considered an indirect measure of quality. Devel::Cover is now quite stable and provides many of the features to be expected in a useful coverage tool. Statement, branch, condition, subroutine, and pod coverage information is reported. Statement and subroutine coverage data should be accurate. Branch and condition coverage data should be mostly accurate too, although not always what one might initially expect. Pod coverage comes from Pod::Coverage. If Pod::Coverage::CountParents is available it will be used instead.Starting Price: Free -
5
LuaCov
LuaCov
LuaCov is a simple coverage analyzer for Lua scripts. When a Lua script is run with the luacov module loaded, it generates a stats file with the number of executions of each line of the script and its loaded modules. The luacov command-line script then processes this file generating a report file which allows one to visualize which code paths were not traversed, which is useful for verifying the effectiveness of a test suite. LuaCov includes several configuration options, which have their defaults stored in src/luacov/defaults.lua. These are the global defaults. To use project specific configuration, create a Lua script setting options as globals or returning a table with some options and store it as .luacov in the project directory from where luacov is being run. For example, this config informs LuaCov that only foo module and its submodules should be covered and that they are located inside src directory.Starting Price: Free -
6
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 -
7
grcov
grcov
grcov collects and aggregates code coverage information for multiple source files. grcov processes .profraw and .gcda files which can be generated from llvm/clang or gcc. grcov also processes lcov files (for JS coverage) and JaCoCo files (for Java coverage). Linux, macOS and Windows are supported.Starting Price: Free -
8
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 -
9
test_coverage
pub.dev
A simple command-line tool to collect test coverage information from Dart VM tests. It is useful if you need to generate coverage reports locally during development.Starting Price: Free -
10
coverage
pub.dev
Coverage provides coverage data collection, manipulation, and formatting for Dart. Collect_coverage collects coverage JSON from the Dart VM Service. format_coverage formats JSON coverage data into either LCOV or pretty-printed format.Starting Price: Free -
11
cloverage
cloverage
Cloverage uses clojure.test by default. If you prefer use midje, pass the --runner :midje flag. (In older versions of Cloverage, you had to wrap your midje tests in clojure.test's deftest. This is no longer necessary.) For using eftest, pass the --runner :eftest flag. Optionally you could configure a runner passing :runner-opts with a map in project settings. Other test libraries may ship with their own support for Cloverage external to this library; see their documentation for details.Starting Price: Free -
12
Slather
Slather
Generate test coverage reports for Xcode projects & hook it into CI. Enable test coverage by ticking the "Gather coverage data" checkbox when editing a scheme.Starting Price: Free -
13
NCover
NCover
NCover Desktop is a Windows application that helps you collect code coverage statistics for .NET applications and services. After coverage is collected, Desktop displays charts and coverage metrics in a browser-based GUI that allows you to drill all the way down to your individual lines of source code. Desktop also allows you the option to install a Visual Studio extension called Bolt. Bolt offers built-in code coverage that displays unit test results, timings, branch visualization and source code highlighting right in the Visual Studio IDE. NCover Desktop is a major leap forward in the ease and flexibility of code coverage tools. Code coverage, gathered while testing your .NET code, shows the NCover user what code was exercised during the test and gives a specific measurement of unit test coverage. By tracking these statistics over time, you gain a concrete measurement of code quality during the development cycle.Starting Price: Free -
14
JaCoCo
EclEmma
JaCoCo is a free code coverage library for Java, which has been created by the EclEmma team based on the lessons learned from using and integrating existing libraries for many years. The master branch of JaCoCo is automatically built and published. Due to the test-driven development approach, every build is considered fully functional. See the change history for the latest features and bug fixes. SonarQube code quality metrics of the current JaCoCo implementation are available on SonarCloud.io. Integrate JaCoCo technology with your tools. Use JaCoCo tools out of the box. Improve the implementation and add new features. There are several open-source coverage technologies for Java available. While implementing the Eclipse plug-in EclEmma the observation was that none of them are really designed for integration. Most of them are specifically fit to a particular tool (Ant tasks, command line, IDE plug-in) and do not offer a documented API that allows embedding in different contexts.Starting Price: Free -
15
OpenClover
OpenClover
Balance your effort spent on writing applications and test code. Use the most sophisticated code coverage tool for Java and Groovy. OpenClover measures code coverage for Java and Groovy and collects over 20 code metrics. It not only shows you untested areas of your application but also combines coverage and metrics to find the riskiest code. The Test Optimization feature tracks which test cases are related to each class of your application code. Thanks to this OpenClover can run tests relevant to changes made in your application code, significantly reducing test execution time. Do testing getters and setters bring much value? Or machine-generated code? OpenClover outruns other tools in its flexibility to define the scope of coverage measurement. You can exclude packages, files, classes, methods, and even single statements. You can focus on testing important parts of your code. OpenClover not only records test results but also measures individual code coverage for every test.Starting Price: Free -
16
SimpleCov
SimpleCov
SimpleCov is a code coverage analysis tool for Ruby. It uses Ruby's built-in Coverage library to gather code coverage data, but makes processing its results much easier by providing a clean API to filter, group, merge, format, and display those results, giving you a complete code coverage suite that can be set up with just a couple lines of code. SimpleCov/Coverage track covered ruby code, gathering coverage for common templating solutions like erb, slim, and haml is not supported. In most cases, you'll want overall coverage results for your projects, including all types of tests, Cucumber features, etc. SimpleCov automatically takes care of this by caching and merging results when generating reports, so your report actually includes coverage across your test suites and thereby gives you a better picture of blank spots. SimpleCov must be running in the process that you want the code coverage analysis to happen on.Starting Price: Free -
17
DeepCover
DeepCover
Deep Cover aims to be the best coverage tool for Ruby code. More accurate line coverage, and branch coverage. It can be used as a drop-in replacement for the built-in Coverage library. It reports a more accurate picture of your code usage. In particular, a line is considered covered if and only if it is entirely executed. Optionally, branch coverage will detect if some branches are never taken. MRI considers every method defined, including methods defined on objects or via define_method, class_eval, etc. For Istanbul output, DeepCover has a different approach and covers all def and all blocks. DeepCover doesn't consider loops to be branches, but it's easy to support them if needed. Even after DeepCover is required and configured, only a very minimal amount of code is actually loaded and coverage is not started. To make it easier to transition for projects already using the builtin Coverage library deep-cover can inject itself into those tools.Starting Price: Free -
18
pytest-cov
Python
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 -
19
Xdebug
Xdebug
Xdebug is an extension for PHP, and provides a range of features to improve the PHP development experience. A way to step through your code in your IDE or editor while the script is executing. An improved var_dump() function, stack traces for notices, warnings, errors, and exceptions to highlight the code path to the error. Writes every function call, with arguments and invocation location to disk. Optionally also includes every variable assignment and return value for each function. Allows you, with the help of visualization tools, to analyze the performance of your PHP application and find bottlenecks. Shows which parts of your code base are executed when running unit tests with PHPUnit. Installing Xdebug with a package manager is often the fastest way. You can substitute the PHP version with the one that matches the PHP version that you are running. You can install Xdebug through PECL on Linux & macOS with Homebrew.Starting Price: Free -
20
OpenCppCoverage
OpenCppCoverage
OpenCppCoverage is an open-source code coverage tool for C++ under Windows. The main usage is for unit testing coverage, but you can also use it to know the executed lines in a program for debugging purposes. Support compiler with a program database file (.pdb). Just run your program with OpenCppCoverage, no need to recompile your application. Exclude a line based on a regular expression. Coverage aggregation, to run several code coverages and merge them into a single report. Requires Microsoft Visual Studio 2008 or higher for all editions including the Express edition. It should also work with the previous version of Visual Studio. You can run the tests with the Test Explorer window.Starting Price: Free -
21
PCOV
PCOV
A self-contained CodeCoverage compatible driver for PHP. When PCOV is left unset, PCOV will attempt to find src, lib or, app in the current working directory, in that order; If none are found the current directory will be used, which may waste resources storing coverage information for the test suite. If PCOV contains test code, it's recommended to set the exclude command to avoid wasting resources. To avoid unnecessary allocation of additional arenas for traces and control flow graphs, PCOV should be set according to the memory required by the test suite. To avoid reallocation of tables, PCOV should be set to a number higher than the number of files that will be loaded during testing, inclusive of test files. interoperability with Xdebug is not possible. At an internal level, the executor function is overridden by PCOV, so any extension or SAPI which does the same will be broken. PCOV is zero cost, code runs at full speed.Starting Price: Free -
22
dotCover
JetBrains
dotCover is a .NET unit testing and code coverage tool that works right in Visual Studio and in JetBrains Rider, helps you know to what extent your code is covered with unit tests, provides great ways to visualize code coverage, and is Continuous Integration ready. dotCover calculates and reports statement-level code coverage in applications targeting .NET Framework, .NET Core, Mono for Unity, etc. dotCover is a plug-in to Visual Studio and JetBrains Rider, giving you the advantage of analyzing and visualizing code coverage without leaving the code editor. This includes running unit tests and analyzing coverage results right in the IDEs, as well as support for different color themes, new icons and menus. dotCover comes bundled with a unit test runner that it shares with another JetBrains tool for .NET developers, ReSharper. dotCover supports continuous testing, a modern unit testing workflow whereby dotCover figures out on-the-fly which unit tests are affected by your code changes.Starting Price: $399 per user per year -
23
Testwell CTC++
Testwell
Testwell CTC++ is a powerful instrumentation-based code coverage and dynamic analysis tool for C and C++ code. With certain add-on components CTC++ can be used also on C#, Java and Objective-C code. Further, again with certain add-on components, CTC++ can be used to analyse code basically at any embedded target machines, also in very small ones (limited memory, no operating system). CTC++ provides Line Coverage, Statement Coverage, Function Coverage, Decision Coverage, Multicondition Coverage, Modified Condition/Decision Coverage (MC/DC), Condition Coverage. As a dynamic analysis tool, CTC++ shows the execution counters (how many times executed) in the code, i.e. more than a plain executed/not executed information. You can also use CTC++ to measure function execution costs (normally time) and to enable function entry/exit tracing at test time. CTC++ is easy to use.Starting Price: Free -
24
Cobertura
Cobertura
Cobertura is a free Java tool that calculates the percentage of code accessed by tests. It can be used to identify which parts of your Java program are lacking test coverage. It is based on jcoverage. Cobertura is free software. Most of it is licensed under the GNU GPL, and you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. Please review the file LICENSE.txt included in this distribution for further details.Starting Price: Free -
25
Gcov
Oracle
Gcov is an open-source code-coverage tool.Starting Price: Free -
26
BullseyeCoverage
Bullseye Testing Technology
BullseyeCoverage is an advanced C++ code coverage tool used to improve the quality of software in vital systems such as enterprise applications, industrial control, medical, automotive, communications, aerospace and defense. The function coverage metric gives you a quick overview of testing completeness and indicates areas with no coverage at all. Use this metric to broadly raise coverage across all areas of your project. Condition/decision coverage provides detail at the control structure level. Use this metric to attain high coverage in specific areas, for example during unit testing. C/D coverage provides better detail than statement coverage or branch coverage, and provides much better productivity than more complex coverage metrics.Starting Price: $900 one-time payment -
27
Coverlet
Coverlet
It works with .NET Framework on Windows and .NET Core on all supported platforms. Coverlet supports coverage for deterministic builds. The solution at the moment is not optimal and need a workaround. If you want to visualize coverlet output inside Visual Studio while you code, you can use the following addins depending on your platform. Coverlet also integrates with the build system to run code coverage after tests. Enabling code coverage is as simple as setting the CollectCoverage property to true. The coverlet tool is invoked by specifying the path to the assembly that contains the unit tests. You also need to specify the test runner and the arguments to pass to the test runner using the --target and --targetargs options respectively. The invocation of the test runner with the supplied arguments must not involve a recompilation of the unit test assembly or no coverage result will be generated.Starting Price: Free -
28
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 -
29
Jtest
Parasoft
Meet Agile development cycles while maintaining high-quality code. Use Jtest’s comprehensive set of Java testing tools to ensure defect-free coding through every stage of software development in the Java environment. Streamline Compliance With Security Standards. Ensure your Java code complies with industry security standards. Have compliance verification documentation automatically generated. Release Quality Software, Faster. Integrate Java testing tools to find defects faster and earlier. Save time and money by mitigating complicated and expensive problems down the line. Increase Your Return From Unit Testing. Achieve code coverage targets by creating a maintainable and optimized suite of JUnit tests. Get faster feedback from CI and within your IDE using smart test execution. Parasoft Jtest integrates tightly into your development ecosystem and CI/CD pipeline for real-time, intelligent feedback on your testing and compliance progress.
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