Best Code Coverage Tools for Vim

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Compare the Top Code Coverage Tools that integrate with Vim as of October 2025

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This a list of Code Coverage tools that integrate with Vim. Use the filters on the left to add additional filters for products that have integrations with Vim. View the products that work with Vim in the table below.

What are Code Coverage Tools for Vim?

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 Vim currently available using the table below. This list is updated regularly.

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    Devel::Cover
    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
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  • 2
    Code Intelligence

    Code Intelligence

    Code Intelligence

    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.
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