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.
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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.
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Testwell CTC++
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.
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RKTracer
RKTracer is a code-coverage and test-analysis tool that enables teams to assess the quality and completeness of their testing across unit, integration, functional, and system-level testing, without altering a single line of application code or build workflow. It supports instrumentation across host machines, simulators, emulators, embedded devices, and servers, and covers a broad array of programming languages, including C, C++, CUDA, C#, Java, Kotlin, JavaScript/TypeScript, Golang, Python, and Swift. It provides detailed coverage metrics such as function, statement, branch/decision, condition, MC/DC, and multi-condition coverage, and even supports delta-coverage reports to show which newly added or modified portions of code are already covered. Integration is seamless; simply prefix your build or test command with “rktracer”, run your tests, then generate HTML or XML reports (for CI/CD systems or dashboards like SonarQube).
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