How long do integration tests take?
I write quite thorough integration tests, trying to make sure I cover each feature. On travis-ci, the entire process takes 25-30 minutes to run (including installing the bundle).
How do you speed up Spring integration testing?
Add an ORM and a few modules and it will quickly skyrocket to 7+ seconds. Add a bunch of profiles, and scatter them through a few tests and we’ll quickly get a 60+ seconds build (assuming we run tests as part of our build – and we should).
How can integration testing be improved?
6 best practices for continuous integration
- Do integration testing before unit testing.
- Don’t test business logic with integration testing.
- Know why integration testing is different from unit testing.
- Keep your testing suites separate.
- Log extensively.
- Don’t stop at integration testing.
What are the best practices for test automation?
As a consequence, we glossed over other things like decoupling, high cohesion, and test automation—all things that have become accepted best practices. You can only do so much with the time and resources at hand.
When to use setup method or teardown method?
Besides the fact that this is an integration test as opposed to a unit test, the operations you describe typically go in Setup and/or Teardown methods. Frameworks like nUnit allow one to decorate class methods with these attributes to indicate whether the method is a setup method or teardown method.
Why do Stack Overflow not follow best practices?
In order to get the most performant site possible when building the codebase for our public Stack Overflow site, we didn’t always follow best practices. Update: I realize we didn’t add a lot of context here when telling the story of the engineering decisions we made years ago, and why we’re moving away from some of them now.
Why are high level languages slower than low level languages?
High-level languages provide safety but have a lot more runtime overhead, so can be slower. Our codebase works the same way. We’ve optimized for speed, so some parts of our codebase used to look like C, because we used a lot of the patterns that C uses, like direct access to memory, to make it fast.