Category: Testing

Rethinking Mocking: DIY Approach vs. Frameworks on examples in PHP and Typescript

In the landscape of software testing, the choice between a do-it-yourself (DIY) approach to mocking or utilizing mocking frameworks is a pivotal decision for programmers. While mocking is indispensable for code reliability, its overuse or incorrect implementation can introduce complexities and fragilities within test suites. This article navigates the balance between leveraging mocks effectively and avoiding common pitfalls, including the dangers of writing mocks in a suboptimal manner.

Tips for optimizing integration tests

While unit tests are known for their speed compared to integration tests, the latter offer heightened confidence in the system’s functionality. Thus, avoiding integration tests is not advisable; instead, it’s crucial to strike a balance by writing tests at an appropriate level to ensure high confidence in the codebase. Achieving this equilibrium between time efficiency and confidence is paramount. Rapid feedback is essential for a smooth workflow, and today, I’ll share concise tips to enhance the efficiency of your integration tests. The effort invested is worthwhile, as swift feedback is indispensable for seamless operations, and each minute of improvement is magnified by the frequency of executions and the number of developers in the company.

Unit testing tips by examples in PHP

In these times, the benefits of writing unit tests are huge. I think that most of the recently started projects contain any unit tests. In enterprise applications with a lot of business logic, unit tests are the most important tests, because they are fast and can us instantly assure that our implementation is correct. However, I often see a problem with good tests in projects, though these tests’ benefits are only huge when you have good unit tests. So in these examples, I will try to share some tips on what to do to write good unit tests.

Mutation testing – we are testing tests

Writing tests should assure us that the code created by us is working correctly. Often we point out the code coverage factor and if we have 100% we can say that implemented solutions are correct. Are you sure? Maybe there is a tool that can give us more accurate feedback?