You go into the code-base, with only a couple of ideas of how the system works. You see a couple of tests, but you quickly sense, these are not great tests. They don't check what really needs to be checked. Things are not set up correctly.
"What were they thinking?", you ask. "The system doesn't work like that."
But how does the system work? What kind of inputs are needed for our specific test? Are you running with an uninitialized database, or is it already filled with data? And is it the right data? These are all decisions that need to be implemented correctly. Assuming you want your tests to be effective.
What does it take to implement data models for tests? In this workshop, you're going to find out.
You'll meet a code-base, with a couple of tests. But you need to implement more from a test plan. And you'll need to use your data modeling mastery to configure the system properly, prepare the right input data, define the assertion information and write the tests.
Then you watch them pass. And then you explain to the team: "This is how the system works".
*The tests will be written in TypeScript, but the data modeling patterns are language agnostic.
