Gain insights into property-based testing with PropEr in Elixir. Learn foundational principles, custom data generators, and advanced concepts for effective real-world application testing.

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Property-based testing relies on specifying some property of code, unlike unit tests, which specify the expected output in response to some inputs. In this course, we'll cover the concepts we need to feel confident about using even the most advanced features of PropEr with Elixir.

We'll start with the basic and foundational principles of property-based testing, see what the framework offers us to get started, make our way through thinking in properties, write our own custom data generators, and then learn more advanced concepts. We'll also see how you can use property-based testing in a realistic project.

By the time we finish this course, we should feel comfortable testing real-world applications using properties.

Property-Based Testing with PropEr in Elixir

# The preconditions
Let's start off by taking a look at the `preconditions`.

```elixir
### Picks whether a command should be valid
def precondition(:unregistered, :ok, _, {:call, _, call, _}) do
  call == :success
end
def precondition(:ok, to, %{errors: n, limit: l}, {:call, _, :err, _}) do
  (to == :tripped and n + 1 == l) or (to == :ok and n + 1 != l)
end
def precondition(
      :ok,
      to,
      %{timeouts: n, limit: l},
      {:call, _, :timeout, _}
    ) do
  (to == :tripped and n + 1 == l) or (to == :ok and n + 1 != l)
end
def precondition(_from, _to, _data, _call) do
  true
end
```

Notice how both calls to erroneous cases are only valid in mutually exclusive instances:

- `(to == :tripped and n + 1 == l)` means that the switch to the `tripped` state can happen if the next failure (the one being generated) brings the total to the limit `l`.
- `(to == :ok and n + 1 != l)` means our state machine can only transition to the `ok` state if this new failure does not reach the limit.

All other calls are valid, since they only transition from one possible source state to one possible target state, and the circuit breaker requires no other special cases. Using an FSM property simplified this filtering drastically compared to what we’d have with a regular stateful property.

Next, we need to perform the data changes after each command. 

# The `next_state_data`
For the data changes after each command, we mostly have to worry about error accounting. Let's take a look at how it's done:


```elixir
### Assuming the postcondition for a call was true, update the model
### accordingly for the test to proceed
def next_state_data(:ok, _, data = %{errors: n}, _, {_, _, :err, _}) do
  %{data | errors: n + 1} 
end
def next_state_data(:ok, _, d = %{timeouts: n}, _, {_, _, :timeout, _}) do 
  %{d | timeouts: n + 1}
end
def next_state_data(_from, _to, data, _, {_, _, :manual_deblock, _}) do
  %{data | errors: 0, timeouts: 0} 
end
def next_state_data(_from, _to, data, _, {_, _, :manual_reset, _}) do 
  %{data | errors: 0, timeouts: 0}
end
def next_state_data(_from, _to, data, _res, {:call, _m, _f, _args}) do
  data
end
```

Error and timeout calls both increment their count by `1`, and deblocking and resetting them move back to `0`. Everything else should have no impact on the data we track.

# The postcondition
Finally, we have the `postcondition`. This one is slightly trickier. 


Complete the test module with the stateful generators and take a look at the completed test suite.

Modeling the Circuit Breaker: The Test Module

Foundations of Property-Based Testing

Writing Properties

Thinking in Properties

Custom Generators

Responsible Testing

Properties-Driven Development

Shrinking

Stateful Properties

Case Study: Bookstore

State Machine Properties

Conclusion

Modeling the Circuit Breaker: The Test Module

The preconditions