AI Generated Tests that actually work!

  I want to share the story of how our team at a fast-paced startup tackled the challenge of API testing without any dedicated QA team, the roadblocks that we encountered, and how we ultimately addressed these issues. Baseline Challenge We had 15-day sprints including mandatory unit and API testing. Strict Timelines (2 weeks) 80% unit test and API test mandate Initially, we relied on automated testing. Unit tests were stable, but API scripts quickly outdated due to frequent data changes and complex scenarios. Lacking a clear evaluation metric like code-coverage in unit tests, we wanted to cover as many user-scenarios possible for APIs. I suggested the record-replay technique for creating disposable API tests. In short, for API tests I wanted: Close to real-world API tests (ideally from prod) Easy disposable tests - quickly create/discard Automatic Infrastructure spin-up or service/dependency virtualization.. Writing test automation script was not an option since we got only 15 days...

  In our previous blog, we explored how to build a modern web server using BunJs and Prisma, integrating robust authentication mechanisms with JWT tokens. Now, it's time to ensure our application is reliable and error-free through thorough testing. In this blog, we'll dive into testing methodologies using Cucumber JS and Keploy, both are a powerful tools that streamline the testing process and enhance the quality of our application. Understanding the Importance of Testing By systematically executing test cases, developers can uncover bugs and errors early in the development process, preventing costly issues in later stages.  For instance , in our BunJs web application, thorough testing would involve scenarios such as user authentication, post creation, and database interactions. By testing each feature extensively, developers can verify that user authentication works as expected, posts are created and retrieved accurately, and database queries return the correct results. And t...