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Code Coverage Best Practices for Frontend Apps

Code Coverage Best Practices for Frontend Apps

As software codebases grow, the need for extensive automated testing becomes more critical 📍 Code coverage is a key metric that measures how much of your source code is tested. It evaluates the percentage of the source code that will be executed when a particular test suite is executed.

This metric is quite useful in accessing the quality of the test suite and identifying potential gaps in it. A codebase with a high code coverage has more of its source code executed during testing which assures the programmer that the chances of it containing an undetected bug are much lower.
This post will talk about the best practices for achieving high code coverage in frontend applications.

Code Coverage Best Practices

In this section, we will go over some of the best practices to keep in mind while trying to improve the test coverage for your application: 

Focus on test quality instead of quantity

Very high code coverage doesn’t necessarily guarantee that the software is free of any bugs. It is important to focus on writing good quality test suites instead of writing tests just for the sake of improving the coverage.
Focusing on just the coverage metric leads to multiple issues, from wasteful machine execution cycles to the problem of maintaining low yield test cases in the future. 
The focus should be to cover as many code paths as possible instead of trying to cover all the lines of code 👨‍💻
In addition to the happy scenario, care must be taken to add test cases that cover exceptional scenarios, which are difficult to reproduce manually. 

Work on improving code coverage across the board

Instead of aiming for very high code coverage for a single code base, work must be done to reach an acceptable coverage limit for all projects. Let’s say your organization sets 60% as an acceptable coverage limit.
The engineering teams should strive to achieve this limit for all the projects instead of focusing on reaching a very high coverage for a single project. Moreover, business needs could differ from project to project, so setting a different acceptable coverage limit for different projects should be encouraged.

Make sure that frequently changing code is well covered

In addition to the project-level code coverage limit, it is a good practice to enforce a commit-level code coverage so that any changes have good code coverage. The general practice is to set a 90% limit for new commits 💹 

Include system/integration tests 

Unit tests are important as they allow testing of an individual function in isolation. In addition to it, integration tests are equally important since it provides a holistic picture of coverage. In some scenarios where multiple services are involved, integration tests assure that inter-service integration is working as expected. 

Avoid duplicating implementation logic

While writing tests, special care must be taken to not duplicate the implementation logic for the test suite. The original implementation should be reused as far as possible.
If you are running into issues using your original implementation, it might be a sign of a code smell. In such scenarios, make sure that your code is following the SOLID principles

Write deterministic test cases

Tests should depict the same behavior as long as the corresponding code hasn’t changed. For example, if your test case is for a function getAge(), the test case should always pass as long as the implementation for the function doesn’t change.
If the test sometimes passes and sometimes fails, then the programmers won’t be able to trust the test and would perceive it as random.

Automate code coverage reports with your CI/CD pipelines

It is essential to integrate the generation of test coverage reports with your CI/CD pipelines to increase visibility and reduce developer effort. Moreover, you can use the pipelines to enforce build rules that fail a particular build if the project level or commit level coverage limit is not met.
It also makes the deployment process much more reliable, as it provides the assurance that builds will pass only if all the test cases pass.

Conclusion

The key takeaway is to focus on the quality of the test cases rather than quantity, and to ensure that the test suite covers all the edge cases. A robust test suite is essential to build confidence during development which leads to faster deployment cycles 🔁

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About the author

Vivek Maskara

Vivek Maskara recently completed his Masters in Computer Science from Arizona State University. He loves writing code, developing apps, creating websites, and writing technical blogs about his experiences. Prior to joining ASU, he worked as an SDE at Zeta, India, and volunteered for the Wikimedia Foundation in his free time.

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