Best Code Coverage Tools for Mac - Page 2

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.

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.

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.

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.

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.

The LDRA tool suite is LDRA’s flagship platform that delivers open and extensible solutions for building quality into software from requirements through to deployment. The tool suite provides a continuum of capabilities including requirements traceability, test management, coding standards compliance, code quality review, code coverage analysis, data-flow and control-flow analysis, unit/integration/target testing, and certification and regulatory support. The core components of the tool suite are available in several configurations that align with common software development needs. A comprehensive set of add-on capabilities are available to tailor the solution for any project. LDRA Testbed together with TBvision provide the foundational static and dynamic analysis engine, and a visualization engine to easily understand and navigate standards compliance, quality metrics, and code coverage analyses.

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.

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.

Gcov is an open-source code-coverage tool.

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.

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.

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.

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.

Our platform uses various security techniques, including coverage-guided and feedback-based fuzz testing, to automatically generate millions of test cases that trigger hard-to-find bugs deep within your application. This white-box approach protects against edge cases and speeds up development. Advanced fuzzing engines generate inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Uncover true vulnerabilities only. Get the input and stack trace as proof, so you can reliably reproduce errors every time. AI white-box testing uses data from all previous test runs to continuously learn the inner-workings of your application, triggering security-critical bugs with increasingly high precision.