Let's define code coverage before we get into various tools.
When you run an automated test, and it succeeds, how can you be sure that the testing tools have examined the entire code? How can you determine the extent to which your code has been executed or covered? That's where code coverage comes into play.
The code coverage is a measure of how much code is executed during the test. It can be determined by code coverage tools that you can integrate into testing tools. They typically throw a percentage value as a coverage result. If it's 100 percent, you don't need to worry; the testing tool has scanned the entire code.
However, if it's below 100%, the code still needs to be thoroughly inspected. If your code still needs to be fully tested, how can you be sure it will work properly? By now, you probably have understood the importance and usefulness of code coverage tools.
Code coverage is as essential as code testing, as incomplete testing can lead to application failures. This article focuses on Java and Node so we will look at code coverage tools for Java and Node.js.
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Code coverage tools merge and integrate with testing software to provide developers with a measure of tested code. They essentially show you how much of your code actually ran during the test. Additionally, they can seamlessly integrate with DevOps code quality tools to provide more detailed results.
As you run your tests, these tools analyze and calculate the code executed. Plus, if you run different tests, they can churn out separate reports for each in one file. A good tool will provide you with a report of various testing such as unit, integration, functional, end-to-end, etc.
In this article, we'll present our top choices for Java and Node.js code coverage that we recommend you explore. Here are our selected options.
JaCoCo stands for Java Code Coverage. It is an open-source code coverage library and free tool based on Java bytecode. JaCoCo provides information about code coverage in various formats, such as HTML, XML, CSV, and JaCoCo execution data files (*.exec).
In addition, it offers customizable color coding to highlight fully, partially, and uncovered lines. This feature applies to your own source code as well as sources linked to instrumented external libraries. Furthermore, JaCoCo supports various JVM languages and is compatible with all released Java class file versions.
The tool tracks each instruction, showing which lines or branches were executed and which were missed during testing. Clicking on the report allows you to identify uncovered and partially covered portions, among other details.
To use JaCoCo, you typically add it as a plugin to your build tool. For example, in a Maven project, you can include it in your pom.xml:
Alternatively, it can be used with Gradle:
You can then run your tests as usual, and JaCoCo will generate a coverage report in the target/site/jacoco directory.
To set up Cypress code coverage, you need to install the @cypress/code-coverage package and configure Cypress to use it. Here's how you can do it:
Next, in your Cypress configuration file (e.g., cypress.json), add the following:
In your plugins file (e.g., cypress/plugins/index.js), include the code coverage plugin:
With this setup, run your Cypress tests as usual, and code coverage reports will be generated in the coverage directory.
First, you need to install nyc globally or locally in your project:
You can then use NPX to run your tests with code coverage like this:
Replace mocha test.js with your testing command. nyc will generate code coverage reports in the ./coverage directory by default.
While code coverage tools offer valuable insights, they can only tell you "what" was tested, not "how well." Uncover the true depth of your Java code's resilience with an expert on your side. Hire a Java expert today and experience the peace of mind that comes from meticulous, human-powered testing.
While we don't rank these tools in terms of popularity, each tool serves a specific purpose. One may excel in unit testing, while another may be more suitable for testing enterprise-grade applications but not as well-suited for more straightforward tests. The choice of a tool ultimately depends on your project's objectives.
In summary, a higher coverage percentage indicates more thorough app testing. If it reaches 100 percent, every aspect has been tested, resulting in a comprehensively tested app. We hope you find this post informative and valuable.
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