How do you boost your front-end code's test coverage?

Boosting your test coverage starts with picking the right tools for your front-end testing. Think of it as finding the perfect tool for a specific framework. 1: Consider project size and complexity, like choosing tools for a DIY project. 2: Make sure compatibility with different browsers. 3: Seek a tool that smartly integrates into your workflow.

as I engineer, I've always enjoyed working as a front-end with many idea's tool based on project size, complexity, framework, browser compatibility, and testing preferences. make it as easy setup, usage, and integration with codebase and workflow. tools include Jest, Mocha, Jasmine, Cypress, Selenium, etc...

The key to boosting your front-end code coverage is to leverage the tools at your disposal as well as following best practices. Writing tests can be time consuming but for component testing, creating util wrappers with all necessary providers (react-query, react-i8n, react-router, etc...) will allow you to focus on writing the tests you need instead of spending time fixing test errors. Tools like Github's Copilot can help speed up your workflow by writing a lot of the boilerplate code needed. Just write a couple of comments stating your test and watch Copilot write most if not all of them for you.

Your front-end testing tools affect your test coverage. You need to pick the ones that match your project. For example, Jest is good for React, while Selenium or Cypress can test across browsers and devices. The right tools can help you automate your testing, avoid errors, and improve your code quality and user experience.

Write clean code would be the first step to make sure your testing process won't consume too much of your time. Make sure to write pure functions as much as possible, it will make your code predictable and easier to test. Try to generate automatic test case, maybe use AI to help you with that. Remove dead/unused code. Remove redundant/cloned code. Add tests to every new code and testing for edge situations.

When i coded fulltime I really enjoyed writing tests. I learnt a new codebase by stepping through breakpoints in tests. Two principles 1. focus on *use case coverage* instead of obsessively increasing *code coverage*. You can game the system by writing meaningless tests that don't resemble how software will be used. 2. UI components often rely more heavily on surrounding components. Unit tests with mock data are not as effective. Write more end-to-end tests and integration tests. This gives you confidence in how the user will use your product.

The testing pyramid underscores the balance between test granularity, speed, and cost. With unit tests at the base, they're quick, plentiful, and ensure individual code pieces function right. Integration tests, in the middle, validate code interactions, bridging isolated checks with holistic views. The apex, end-to-end tests, simulate full application use-cases but are slower and costlier. The pyramid's shape emphasizes that while a broad foundation of unit tests is essential, fewer, critical end-to-end tests at the top can maximize coverage and minimize overhead. Adopting this ensures efficient, effective testing across projects.

End-to-End Tests (Top of the Pyramid): Include end-to-end tests using Cypress to simulate user workflows and validate the entire application's functionality. While fewer in number, these tests offer high-level coverage, ensuring a smooth integration of all components in a real-world scenario.

Try to follow the testing pyramid and assemble the team to prioritize the use cases and, consequently, pyramid prioritization. Ordering your tests from the pyramid of "Must Have," "Should Have," and Nice to Have could help you achieve better results.

There are some peculiarities when creating tests in large applications where many development teams are involved. If you are a new feature developer, then your task is to focus on unit testing and pay as much attention to this aspect as possible. The integration testing stage can no longer be handled by the developer himself, but by an automated testing engineer, but often this is also the responsibility of the developer. End-to-end tests is testing engineer's responsibility. The smaller the application, the more the developer devotes to creating all stages of the testing pyramid. For example, in small applications, in addition to these type of tests, the developer can also do manual testing in the absence of a testing engineer on site.

To increase front-end code test coverage effectively and maintain productivity: 1. Start small, focusing on critical code segments and UI. 2. Choose suitable testing tools for your team's needs. 3. Automate tests for long-term efficiency. 4. Write code that's easily testable with clear variable names and comments. 5. Test continuously throughout development, not just at project end. 6. Seek assistance from team members or online communities when needed. 7. Patience and persistence are vital for successful testing; it's an investment in code quality. Testing improves code quality, boosts confidence, and pays off in the end. Don't give up on it!

Along with the mentioned pointers, you should keep this in mind. Often we end up writing not so useful test cases, and think we are increasing test coverage, which is ideally the opposite of what you are trying to achieve, which is writing efficient test cases. The essence here is, to think what the user is going to be testing on your product. And write your test cases on the same. Be it correct functionality of the button, when clicked or something else. It shouldn't be just checking whether button present, text present, and just make the test cases looks bulky.

Stay DRY; Embrace Helpers 🌵 Another saying goes like this No Man IS an Island . So let us all remember and repeat after me: "I won't repeat myself!" An old classic, where we find ourselves going in circles, Yes I’m talking to you. We have all been there there young and old. Stop for a minute and have a Birds Eye View (BEV) If there are common patterns in our tests, then we abstract them into helper functions or ask for help. Here, we are saved. I can assure you that our future self will thank us for doing so

- If you start writing tests recently keep an eye on how you are structuring the code after having the habit of writing testable components (unit tests). You will find that you are relying more on Solid principles. This is a thing of becoming more an Engineer than a code writer. - We are not writing tests to pass the pipeline, we are writing tests for the sake of code base/quality/ keeping your code safe against changes/etc...

Just a word of caution: achieving 100% coverage shouldn't be the end goal, but rather ensuring that critical paths and functionalities are adequately tested. It's about meaningful coverage over just numbers.

In addition to 'nyc' I can recommend Sonar tool. This is a tool not only for coverage reports and test execution reports, but it is also a powerful linter.

I will say , start with the Basics: Test What Matters 🎯 With this I will say begin, asking yourself what you are developing: What are the core functionalities which needs to be rock solid?The Focus should be on these critical paths first. Do not get lost trying to get 100% coverage. No one is perfect the decision of a good product lies with the end users whom we are developing for. Thus, ensure that the 20% of your code that does 80% of the work is airtight.

Sure! Here are the basic steps involved in TDD: 1: Write a test: Start by writing a test for a small piece of code, including the expected outcome. 2: Run the test: Run the test to see if it fails. 3: Write the code: If the test fails, write the minimal amount of code needed to make the test pass. 4: Refactor the code: Once the test passes, refactor the code to make it more efficient and readable. 5: Repeat the process: Continue writing tests, running them, and refactoring the code until all features have been developed and tested. By these following steps, TDD helps to ensure that your code is tested thoroughly and is of high

Resources for Learning Test-Driven Development (TDD) Online courses: Many online courses are available to teach TDD. Some popular options include Udemy, Coursera, and edX. Books: There are also many books available on TDD. Some popular options include "Test-Driven Development by Example" by Kent Beck and "Growing Object-Oriented Software, Guided by Tests" by Steve Freeman and Nat Pryce. Official documentation: The official documentation for popular testing frameworks can also be helpful. For example, the official documentation for Jest (JavaScript), JUnit (Java), and PyTest (Python) can be found online. Practice: The best way to learn TDD is to practice it. Try applying TDD to small coding exercises or personal projects.

The main crux of following a TDD is to use this method: Red-Yellow-Green. What you have to do is, first write the test case which fails (which is Red), and then once that is working as expected, improve the test case, and re-check for any other issues (which is Yellow), once that is done, you finally get the idea, and then write the test case which passes your expectations (which is Green).

Antoine de Saint-Exupéry once said, "A designer knows he has achieved perfection not when there is nothing left to add, but when there is nothing left to take away." The same principle applies to refactoring your code during TDD. Write what you need to write to make the feature work, and then think: - Are there redundancies in this script? - Can I refactor this code to be more performant? - What built-in tools, objects, or functions are available to help me solve this problem in a more native way?

Plan ahead: 1. What problems is your code solving? - answering this should help structure your code for TDD. 2. What are some edge cases/blind spots that you can identify right now? 3. Risk analysis: you can plan ahead of risk by writing tests that validate a risk hypothesis and see how that performs post-prod. Good luck!

Given that front end development is ultimately oriented around creating a usable UX/UI, it pays back to write tests in a way mimicking the user's real interactions. Being able to query for visible labels or accessibility properties will ensure not only that the components behave in a desired way, but also that everyone - able and less able users - will interact with thoroughly tested interface. Querying for test IDs or specific props will result in testing the implementation details only, but will not guarantee that the component is truly usable.

Resources for Learning Test-Driven Development (TDD) for React JS Online courses: Some popular options include: "TDD with React JS" on Udemy "React TDD with Jest" on Coursera "TDD for React" on edX Books: Some popular options include: "Test-Driven Development with React" by Kent Beck "React Testing Library" by Kent C. Dodds and Jessica Kerr Official documentation: The official documentation for popular testing frameworks can also be helpful. For example, the official documentation for Jest and React Testing Library can be found online. Practice: The best way to learn TDD is to practice it. Try applying TDD to small coding exercises or personal projects.

🔍 Understand the Problem Before Solving It Before diving into lines of test code, it’s vital to understand what problem you are trying to solve. Are you looking to identify edge cases? Do you want to ensure seamless user experience? Or is your goal to make the code more maintainable? By defining the problem clearly, you can tailor your tests to be more effective and efficient. Don’t lose sight of the rationale behind testing. Knowing 'why' sets the stage for a more robust, reliable, and meaningful 'how.'

You should not have to pay to learn web development. There are endless free resources available to you for learning. For example, Scrimba is an amazing resource for learning front-end web development, including React. Bob Ziroll is one of the top instructors in the world. And best of all the course is available absolutely free.

While TDD might seem slower initially, it's a learning curve. As you master it, the initial time investment pays off with quicker development, reduced debugging, and enhanced code quality. It's about short-term patience for long-term speed and reliability.