crafting (and) JavaScript

Tagged with #testing

In part 1 I started my naive investigation on how to apply machine learning for making visual regression tests (VRT) better. I described the problem to solve, explored Keras very superficially and did also touched on the complexity of doing ML myself as opposed to having colleagues who are experts and who throw phrases like "train a model" and "predict" etc. around.
Oh boy, did I underestimate this.

While refactoring some badly tested code, a pattern of how I extract dependencies emerged. The actual intention was to improve the testability. In this case dependency injection is the tool that helped me. Read here to find out the steps I found to separate the dependencies.

IDEs are awesome, but sometimes in my way and setting up test runners sometimes defeats the purpose of being fast with tests, which also means having feedback constantly and continuously.