Open Source Linux Code Coverage Tools - Page 2

bcov is a code coverage tool similar to gcov. Unlike gcov, it does not require recompiling the project for coverage. Coverage is determined by using temporary breakpoints, which causes minimal overhead. gcov produces a lcov style coverge report.

High-quality, modular starter project for Angular 2 (and beyond) with statically typed build and AoT. Allows you to painlessly update the seed tasks of your already existing project. Supports multiple Angular applications with shared codebase in a single instance of the seed. Official Angular i18n support. Ready to go, statically typed build system using gulp for working with TypeScript. Production and development builds. Ahead-of-Time compilation support. Sample unit tests with Jasmine and Karma including code coverage via Istanbul. End-to-end tests with Protractor. Development server with Livereload. Following the best practices. Manager of your type definitions using @types. Has autoprefixer and css-lint support. Provides full Docker support for both development and production environment.

The Automatic JUnit Creation Tool analyzes java classes to map all possible test branches. The tool then guides users through the generation of a JUnit test.

BeCover is a Java code coverage tool based on source-code analysis. The main goal is to keep it small and fast, so using it as a plugin in the common IDE's can be achieved.

This project provides a meaningful way to increase code coverage of your jUnit and TestNG tests. Unit testing Java Beans can be a tedious task. The goal of this project is to provide an automated way to unit test the getters and setters of a class.

Boilerplate and Starter for Next JS 12+, Tailwind CSS 3 and TypeScript. Boilerplate and Starter for Next.js, Tailwind CSS and TypeScript. Made with developer experience first: Next.js, TypeScript, ESLint, Prettier, Husky, Lint-Staged, Jest, Testing Library, Commitlint, VSCode, Netlify, PostCSS, Tailwind CSS. If you are VSCode users, you can have a better integration with VSCode by installing the suggested extension in .vscode/extension.json. The starter code comes up with Settings for a seamless integration with VSCode. The Debug configuration is also provided for frontend and backend debugging experience. With the plugins installed on your VSCode, ESLint and Prettier can automatically fix the code and show you the errors. Same goes for testing, you can install VSCode Jest extension to automatically run your tests and it also show the code coverage in context.

Cov is a code coverage tool to get your code coverage after your runuing some steps for your programs.It is based on llvm(Low Level Virtual Machine,http://llvm.org/).Now,it's only a begining,so welcome anybody to join in.

Catberry is an isomorphic framework for building universal front-end apps using components, Flux architecture and progressive rendering. Catberry builds a bundle for running the application in a browser as a Single Page Application. Cat-Components – similar to web-components but organized as directories, can be rendered on the server and published/installed as NPM packages. The entire architecture of the framework is built using the Service Locator pattern, which helps to manage module dependencies and create plugins, and Flux, for the data layer. Search crawler receives a full page from the server. The whole state of the application is restored from URL. Server-side progressive rendering based on node.js streams and parallel rendering of components in a browser. The framework is well-tested (code coverage is about 90%) and it is already used in production.

Sonar offers a single cohesive solution with a consistent set of metrics and hundreds of static analysis rules to detect your coding issues early. Plus fast and high-precision analysis means high value, low noise, and reliable results always. A single solution for dozens of popular languages, development frameworks and IaC platforms. Our powerful language-specific analysis not only detects coding issues but also helps you understand what's wrong and how to fix it. Our publicly available ruleset includes thousands of rules covering various issue categories and language standards. Open the rule in SonarQube / SonarCloud, scroll down and (in case the rule has parameters), you can configure the parameters for each Quality Profile the rule is part of. Standalone NuGet packages can be configured the same way as SonarLint in connected mode.

An eclipse plugin for code coverage visualization of JUnit Tests. Especially useful for test-first development. Supported coverages include block coverage and all-uses coverage (Data Flow Analysis).

EL4Ant is a light and efficient build system based on Apache Ant. A project is described in XML as modules with transitive dependencies. Features are provided thanks to plugins: Java execution, JUnit reports, EMMA code coverage, Eclipse integration...

Easy Coverage is a tool that can dynamically generate unit tests to perform basic verifications, thus leaving more time for the developers. When writing unit tests, developers often have to write the same elementary verifications over and over for most classes. This is tedious and error-prone, and keeps developers away from writing more meaningful unit tests. Easy Coverage is extensible and highly configurable. It can work as a standalone product, or be used with JUnit, which is highly recommended. Support for TestNG is planned. If you want to get started, you should go to the wiki and the quick start.

A boilerplate application for building RESTful APIs Microservice in Node.js using express and mongoose in ES6 with code coverage and JsonWebToken Authentication. Helps you stay productive by following best practices. Follows Airbnb's Javascript style guide. JavaScript code linting is done using ESLint, a pluggable linter tool for identifying and reporting on patterns in JavaScript. Uses ESLint with eslint-config-Airbnb, which tries to follow the Airbnb JavaScript style guide. Supports code coverage of ES6 code using istanbul and mocha. Code coverage reports are saved in the coverage/directory post yarn test execution. Open coverage/lcov-report/index.html to view the coverage report. yarn test also displays code coverage summary on the console. Code coverage can also be enforced overall and per file as well, configured via .istanbul.yml.

gcov-eclipse is an Eclipse plug-in that will extend CDT to provide code-coverage testing to C/C++ projects by using the gcov program. It will integrate into the CDT's launch and managed build system.

Visualize the distribution of code coverage in your project. This helps to identify code areas with high and low coverage. Useful when you have a large project with lots of files and packages. This 2D image-hash of your project should be more representative than a single number. For each module, the node representing the greatest version (i.e., the version chosen by Go's minimal version selection algorithm) is colored green. Other nodes, which aren't in the final build list, are colored grey — by the official Go team. Use to find unexpected dependencies or visualize the project. Works best for a small number of packages, for large projects use grep to narrow down subgraph. Collect all the licenses or check if you can use the project for example in a proprietary or commercial environment. Tell Go compiler which versions of upstreams to include in your build. Tell all users of your module how to deal with versions of your module.

Hansel is an extension to JUnit implementing code coverage tests.

A cross platform Http web server developed using C++. Agile methodology with emphasis on :- 1. Good Design 2. Object Oriented Programming 3. Refactoring 4. Static/Dynamic Analysis, Unit-testing, Code Coverage 5. Software Engineering best practices.

An integrated testing framework, covering test case generation, execution, bug reporting, code coverage and coding conventions. Currently This is a module suite for netbeans IDE, integrating some open source PHP Testing Tools

JUnitMetrics is a tool that enables to measure basic JUnit and Cactus tests metrics (like number of tests, assertions, number of executed assertions). It is great, complementary solution to code coverage tools and mutation testers.

A Gradle plugin that auto-creates and configures JaCoCo code coverage tasks for each Android app/module variant, saving you from manual setup across build types and flavors.

This profiler (JRE 1.5.0 only) uses JVMTI and native bytecode instrumentation for the analysis of the heap, reachable objects, execution time, garbage collection efficiency, code coverage and thread contention. No preparation steps required in build.

It is a JavaDoc and comment coverage tool. It check the quality of JavaDoc and comments in Java source files. The output is like the EMMA Java code coverage.

Javelina is an advanced code coverage tool that uses dynamic instrumentation to minimize the overhead for collecting coverage data. Additionally, Javelina allows the application of logical operations to code coverage data.

A quick C++ template for modern CMake projects aimed to be an easy-to-use starting point. This is my personal take on such a type of template, thus I might not use the best practices or you might disagree with how I do things. Any and all feedback is greatly appreciated! Modern CMake configuration and project, which, to the best of my knowledge, uses the best practices. An example of a Clang-Format config, inspired from the base Google model, with minor tweaks. This is aimed only as a starting point, as coding style is a subjective matter, everyone is free to either delete it (for the LLVM default) or supply their own alternative. Static analyzers integration, with Clang-Tidy and Cppcheck, the former being the default option. Doxygen support, through the ENABLE_DOXYGEN option, which you can enable if you wish to use it. Unit testing support, through GoogleTest (with an option to enable GoogleMock) or Catch2. Code coverage, enabled by using the ENABLE_CODE_COVERAGE op.

Setting up a new C++ project usually requires a significant amount of preparation and boilerplate code, even more so for modern C++ projects with tests, executables and continuous integration. This template is the result of learnings from many previous projects and should help reduce the work required to setup up a modern C++ project. Installable target with automatic versioning information and header generation via PackageProject.cmake. Automatic documentation and deployment with Doxygen and GitHub Pages. Eventually, you can remove any unused files, such as the standalone directory or irrelevant github workflows for your project. Feel free to replace the License with one suited for your project. To keep the template modular, all subprojects derived from the library have been separated into their own CMake modules. This approach makes it trivial for third-party projects to re-use the projects library code.