Best Code Coverage Tools for Windows

Sahi Pro is a no-code test automation tool for web, desktop, mobile, and SAP applications. Sahi Pro empowers business testers and automation engineers to streamline their test automation processes. Sahi Pro reduces the time, effort, and complexity involved in test automation, making it an ideal choice for various domains including automobile, healthcare and BFSI. Features: 1. Non-flaky Test Execution - For reliable test results and reduced time wastage in analysis of false-positives or false-negatives. 2. Supports Multiple Technologies - Achieve end to end automation across technologies. 3. No-code Automation - Enable non-technical business testers to automate. 4. Integrations - Integrate and work with your existing ecosystem. Testers using Sahi Pro easily automate complex tests without writing code. With Sahi Pro, you can achieve faster release cycles, improved software quality, & reduced costs. Our customers love Sahi Pro for its speed, flexibility, and ease of use.

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.

IntelliJ IDEA analyzes your code, looking for connections between symbols across all project files and languages. Using this information it provides in-depth coding assistance, quick navigation, clever error analysis, and, of course, refactorings. ^⇧Space gives you a list of the most relevant symbols applicable in the current context. This and other completions are constantly learning from you, moving the members of the most frequently used classes and packages to the top of the suggestions list, so you can select them faster. Digs a tad deeper than Smart Completion and lists applicable symbols accessible via methods or getters in the current context. Say you're looking for a value of Project and only have the Module module declaration. Press ^⇧Space twice to get module.getProject() without any additional effort. Static members completion Lets you easily use static methods or constants. Offers a list of symbols matching your input and automatically adds required import statements.

All the Python tools in one place. Save time while PyCharm takes care of the routine. Focus on the bigger things and embrace the keyboard-centric approach to get the most of PyCharm's many productivity features. PyCharm knows everything about your code. Rely on it for intelligent code completion, on-the-fly error checking and quick-fixes, easy project navigation, and much more. Write neat and maintainable code while the IDE helps you keep control of the quality with PEP8 checks, testing assistance, smart refactorings, and a host of inspections. PyCharm is designed by programmers, for programmers, to provide all the tools you need for productive Python development. PyCharm provides smart code completion, code inspections, on-the-fly error highlighting and quick-fixes, along with automated code refactorings and rich navigation capabilities.

On-the-fly error detection and suggestions for fixes, quick and safe refactorings with one-step undo, intelligent code completion, dead code detection, and documentation hints help all Go developers, from newbies to experienced professionals, to create fast, efficient, and reliable code. Exploring and understanding team, legacy, or foreign projects takes a lot of time and effort. GoLand code navigation helps you get around with instant switching to shadowed methods, implementations, usages, declarations, or interfaces implemented by types. Jump between types, files or any other symbols, or find their usages and examine them with convenient grouping by usage type. Powerful built-in tools help to run and debug your applications. You can write and debug tests without any additional plugins or configuration effort, and test your applications right in the IDE. A built-in Code Coverage tool will make sure that your tests don’t miss anything important.

Debugging should be simple. AQTime Pro synthesizes complex memory and performance information into digestible, actionable insights so you can quickly find bugs and their root cause. Finding and squashing highly differentiated bugs is tedious and complicated, but AQTime Pro makes it easy. With over a dozen profilers, you can find memory leaks, performance bottlenecks, code coverage gaps and more in just a few clicks. AQTime Pro enables you to squash all bugs with one tool and get back to making high quality code. Don’t let code profilers box you in with a single codebase or framework and prevent you from finding performance bottlenecks, memory leaks, code coverage gaps unique to your project. AQTime Pro is the one tool to use across multiple codebases and frameworks in a project. It has broad language support for C/C++, Delphi, .NET, Java and more.

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.

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.

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.

Codacy is an automated code review tool that helps identify issues through static code analysis, allowing engineering teams to save time in code reviews and tackle technical debt. Codacy integrates seamlessly into existing workflows on your Git provider, and also with Slack, JIRA, or using Webhooks. Users receive notifications on security issues, code coverage, code duplication, and code complexity in every commit and pull request along with advanced code metrics on the health of a project and team performance. The Codacy CLI enables running Codacy code analysis locally, so teams can see Codacy results without having to check their Git provider or the Codacy app. Codacy supports more than 30 coding languages and is available in free open-source, and enterprise versions (cloud and self-hosted). For more see https://www.codacy.com/

Appvance IQ (AIQ) delivers transformational productivity gains and lower costs in both test creation and execution. For test creation, it offers both AI-driven (fully machine-generated tests) and also 3rd-generation, codeless scripting. It then executes those scripts through data-driven functional, performance, app-pen and API testing — for both web and mobile apps. AIQ’s self-healing technology gives you complete code coverage with just 10% the effort of traditional testing systems. Most importantly, AIQ finds important bugs autonomously, with little effort. No coding, scripting, logs or recording required. AIQ is easy to integrate with your current DevOps tools and processes. Appvance IQ was developed by a pioneering team who envisioned a better way to test. Their innovative vision has been made possible by applying differentiated, patented AI methods to test creation while leveraging today’s high-availability compute resources for massive levels of parallel execution.

The easiest way to unit test. Write tests without changing your code! Even legacy code. Static methods, private methods, non-virtual methods, out parameters and even members and fields. Our professional edition is free for developers around the world. We also have paid support package. Improve your code integrity and deliver quality code. Fake entire object models with a single statement. Mock statics, private, constructors, events, linq, ref args, live, future, static constructors. Our suggest feature creates automated test suggestions suitable for your code. Our smart runner will run only your impact tests and get you super fast feedback. Our coverage feature displays your code coverage in your editor while you code.

Coco® is a multi-language code coverage tool. Automatic source code instrumentation is used to measure test coverage of statements, branches and conditions. Executing a test suite against an instrumented application produces data that can later be analyzed. This analysis can be used to understand how much of the source code has been hit by tests, which additional tests need to be written, how the test coverage changed over time and more. Identify redundant tests, untested or dead code. Identify the impact of a patch on the code and code coverage & your testing. Coco supports statement coverage, branch coverage, MC/DC and other levels. Linux, Windows, RTOS and others. Using GCC, Visual Studio, embedded compilers and more. Choice of different report formats (text, HTML, XML, JUnit, Cobertura). Coco can also be integrated with various build, test and CI frameworks like JUnit, Jenkins and SonarQube.

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.

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.

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.

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.

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.

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.

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.

Mainly, a better-lookin' report UI, a simpler maven configuration. Add the plugin instrumentation settings to child projects and the report merging settings to the parent project.

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.

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.

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.

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.

Linux, Windows, RTOS and others. Using gcc, Visual Studio, embedded compilers and more. Merging multiple execution reports to provide advanced analysis and more outstanding features. Assess and optimize code performance with Coco’s built-in Function Profiler.

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.

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.

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.

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.