How to Use Coverlet Coverage for Improved Code Quality in Testing?

Have you ever considered how well-tested your .NET code simply is? Many teams feel their test suite is complete until a bug makes its way into production. The hard part is not just writing tests, but determining if tests cover critical paths. When using standard coverage tools, coverage can seem convoluted and unrelated to how you write code. This is where Coverlet coverage comes in – a simple to use, open source library for measuring test file coverage, and improving test coverage. In this blog, we’ll understand how coverlet coverage works and take an in-depth view of the coverage report to fill coverage gaps in your overall test strategy for better software stability.

What Is Coverlet Coverage?

Coverlet coverage is an open-source code coverage tool for .NET Core, .NET Standard, and .NET Framework. It interfaces with your testing framework (xUnit, NUnit, MSTest) to display the coverage of your code that your tests end up exercising. Simply put, Coverlet Code Coverage gives you the percentage of lines, branches, and methods exercised while your tests run. It enables teams to ensure they have tested their critical business logic, directly impacting the reliability and maintainability of their software. Unlike older coverage tools, Coverlet does not rely on external dependencies and does not require complex configurations—it fits into your .NET workflow.

Why Test Coverage Matters for Code Quality?

Good test coverage provides validation that your code works – it evaluates the degree tests work. If the coverage testing is insufficiently providing validation, well-written code could still have untested paths or conditions that could fail in the wild. Over time, tracking code coverage can help developers:

• Detect untested or unreachable code sooner

• Identify duplications

• Gives a greater sense of the quality of the code and confidence in releases

• Provides long-term maintainability of the project

Coverlet code coverage can function as a measure for completeness of testing, and Keploy tooling can extend the code coverage by evaluating real traffic to automatically generate test cases to mock APIs. Together, they can help create a tighter feedback loop between measuring with Coverlet, then iterating with Keploy.

How to Use Coverlet Coverage?

Using Coverlet coverage is simple and doesn’t require deep setup knowledge. You can run it from the command line, integrate it into CI/CD pipelines, or use it via the Visual Studio Test Explorer.

1. Install Coverlet

You can install Coverlet using the .NET CLI:

dotnet add package coverlet.collector

This command adds the Coverlet collector to your project, enabling automatic coverage collection during test execution.

2. Run Tests with Coverlet Collector

Once installed, you can run your tests with coverage reporting enabled:

bash
dotnet test --collect:"XPlat Code Coverage"

This command uses the Coverlet collector code coverage feature to track which parts of your application code were executed.

3. View Coverage Results

After running your tests, a coverage file (in .cobertura or .json format) is generated under the TestResults directory. You can use tools like ReportGenerator or CI dashboards to visualize these results.

This Coverlet code coverage report provides detailed metrics such as:

• Line coverage: How many lines were executed

• Branch coverage: Whether all conditions were evaluated

• Method coverage: Which functions were called during tests

Here’s a basic Coverlet coverage example command that exports results:

bash
dotnet test /p:CollectCoverage=true /p:CoverletOutputFormat=lcov

Improving Code Quality with Coverlet Coverage

Generating a report alone does not help; it is the action you’ll take from the report that will really affect code quality in testing. Here’s what you can do to get the most from your coverage numbers:

• Look at low-coverage areas. Shift your testing focus toward methods or modules that have low coverage.

• Relate to production concerns. If there are certain bugs showing up over and over again, you probably want to make sure these modules are being tested with adequate coverage.

• Automate the coverage metrics. Include the Coverlet console commands in your CI/CD so that you are tracking coverage metrics to prevent regressing the coverage numbers.

• Set coverage targets. Aim for goals that make sense (e.g., 80%+) instead of 100%. Fresh thinking should be prioritized over boilerplate code.

By working through these methods and automating test case generation with Keploy you will do a good job building the bridge between measuring and writing tests.

How Coverlet and Keploy Work Together?

While Coverlet demonstrates what is currently tested within the project, Keploy facilitates the end user in automatically generating more tests by simply interacting with the application as an end-user would do while walking through the application.

A common workflow would include the following:

• Start utilizing Keploy to capture the API calls and automatically generate integration tests.

• Run those tests as part of your .NET test suite.

• Measure how much of the backend logic is actually being tested with Coverlet coverage.

• Identify gaps and generate more tests as necessary.

Together, this enhances the confidence that your test automation pipeline is not only scaling, but also improving the accuracy of the coverage and the reliability of your code over time.

The Future of Test Coverage and Automation

Software testing is changing rapidly. Consider Coverlet coverage just the starting point. As engineering teams embrace faster, more frequent release cycles and microservice-based architectures, the demand for intelligent and automated coverage analysis is growing.

The future will look like:

• AI-assisted testing: Not only will tools measure coverage, but they will also automatically suggest new test cases. Keploy is already generating tests from real traffic flows, a scalable version of tomorrow’s test coverage solution.

• Shift-left coverage tracking: Developers will measure and improve test coverage earlier in the development cycle. The use of tools like Coverlet will be integrated directly into IDEs and pre-commit hooks for coverage tracking.

• Smarter coverage metrics: As organizations adopt new coverage measurement models, coverage metrics will go beyond line coverage and branch coverage. More advanced coverage models, like mc/dc testing and mutation coverage, will be adopted for mission-critical systems.

• Unified test platforms: Coverage tools (like Coverlet) will be integrated with test automation frameworks (like Keploy) to form a seamless unified continuous test loop – measure, improve, measure.

As the lines between development (including unit tests) and independent testing become increasingly blurred, tools like Coverlet coverage and automation-first tools (like Keploy) will help teams maintain both speed and quality.

Conclusion

Modern testing goes beyond creating more tests; it’s about creating the right tests. Coverlet coverage allows teams to see exactly where they stand in their testing efforts, and tools like Keploy, thanks to the coverage information, push this boundary even further by automatically creating and managing tests.

The combination of measurement and automation allows your team to achieve better-quality code, greater confidence in releases, along with more effective continuous delivery plans. If you’re new to coverage analysis or looking to improve your testing workflow, becoming proficient in Coverlet coverage is a tangible step toward better and smarter testing.

Frequently Asked Questions (FAQs)

What is a Good Test Coverage Percentage?

Answer: In general, you can expect to see a test coverage percentage of 70% to 90%, depending on the type of project and your risk tolerance for the project type. Again, the aim is never to have 100% coverage. What we really want is appropriate coverage of the critical business logic and the edge cases. Meaningful coverage, that’s your true aim – not coverage for the sake of coverage.

What’s the Difference between Coverlet Test Coverage and Traditional Test Coverage Tools?

Answer: Traditional test coverage tools require significant setup complexity and/or paid licenses (in other words, they are not free). Coverlet is an open source, lightweight tool that is designed to be native to the .NET ecosystem, and provides additional detail metrics such as line, branch, and method coverage right from the command line or CI pipeline.

What Are the Different Output Formats Supported by Coverlet Coverage?

Answer: Coverlet coverage has the advantage of exporting to many formats, including JSON, Cobertura, LCOV, and OpenCover. These formats are all easily used with CI/CD dashboards and report visualizers, or even with third-party tools such as ReportGenerator, which give you a more visual representation of your test coverage.

How Can I Integrate Coverlet Coverage into a CI/CD Pipeline?

Answer: You will want to configure your CI/CD pipeline test job either by adding the Coverlet collector or by executing a console command. For example, in GitHub Actions or Azure DevOps, for example, simply run dotnet test –collect:"XPlat Code Coverage" and it will automatically create coverage reports for each build. This method also maintains a history of coverage between every commit and every PR.