![visual studio code coverage results visual studio code coverage results](http://www.pererikstrandberg.se/blog/testing-visual-studio/54-verify-code-coverage.png)
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We’re not adding anything meaningful here. To simulate this behavior, let’s open a new pull request on our repository, making a slight modification to the “Add” method: public int Add(int one, int two) These are both separate metrics, which are exposed in our code coverage reports respectively.
![visual studio code coverage results visual studio code coverage results](https://devblogs.microsoft.com/devops/wp-content/uploads/sites/6/2015/11/2746.image_thumb_651A54A1.png)
Each team would have its own policies here, but a good recommendation is to ensure that any code should:ī) not drop overall coverage for the repository. In this section, we’ll be looking at how code coverage fits into our quality assurance process. Now that we have a nice tool for exploring our code coverage, in the next section, we’ll look at adding a check into our pull requests to ensure new code doesn’t drop coverage. The Codecov action also has a lot more configuration, but let’s keep the defaults.
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The rest of the steps in the GitHub Actions build file should be self-explanatory, and feel free to read up more on the GitHub documentation.
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![visual studio code coverage results visual studio code coverage results](https://i.stack.imgur.com/jz6pZ.png)
Learning Web API? Get our eBook ASP.NET Core Web API Best Practices and become an expert for FREE! > GET THE BOOK <<īefore we continue, you need to sign in to Codecov with your GitHub account. There are a variety of pricing options outside the scope of this article, but open source code is free, which we’ll use in our example. Code Coverage Reports in Codecov.ioĬodecov.io is a popular commercial tool that lets you get better insights into your code coverage. In the next section, we’ll look at pushing the code coverage results to a service called codecov.io, which puts a nice UI on top of the coverage file, and is helpful for integrating into our build processes, which we’ll see a bit later. This effectively means we now have 100% code coverage! If we run the same dotnet test command as before, and inspect the new “” file, we see different results: Var actual = _calculator.Subtract(one, two) Public void GivenTwoNumbers_Subtract_ReturnsTheFirstNumberSubtractedFromTheSecond() Public void GivenTwoNumbers_Add_ReturnsTheTwoNumbersAddedTogether() Private readonly Calculator _calculator = new Calculator() Next, let’s add a new test class called CalculatorTests.cs, implementing the tests as we’d expect the behavior to occur: public class CalculatorTests Code coverage is generated based on the lines hit, as well as “branches”, which is if our code has statements that have if / else / switch for example, which can result in different paths of execution.
![visual studio code coverage results visual studio code coverage results](https://i.stack.imgur.com/9cB7j.png)
This is as expected since we don’t have any tests yet.
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Theory on Code Coverageīefore we jump into the technical details, it’s worth spending a moment understanding the theory behind code coverage and why it’s important in software development. Let’s jump right into some basic theory on code coverage.
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To download the source code for this article, you can visit our Code Coverage in.