Gain insights into property-based testing with PropEr in Erlang. Delve into foundational principles, common frameworks, custom data generators, and applying testing in realistic projects for robust code validation.

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Property-based testing relies on specifying some property of code, rather than unit tests which specify the expected output in response to some inputs. In this course, you’ll cover the concepts you need to get started, up to the point where you feel confident enough to use the most advanced features of PropEr with Erlang.

You’ll start smoothly with the basic and foundational principles of property-based testing. From there, you will cover some of the common frameworks, how to think in properties, how to write your own custom data generators, and more. You'll also see how you can use Property-Based Testing in a realistic project.

By the time you finish this course, you will be comfortable testing real-world applications using properties.

Property-Based Testing with PropEr in Erlang

# Getting started

Since we have a fairly large stateful system to validate, we should start by figuring out what data the system should accept, and what is valid and invalid. This is useful because it sets a baseline for expectations on which to build. It can also hint at useful paths or strategies moving forward. We’ve got a basic idea about the shape of data based on our database schema.

# The generators

We'll have a total of three generators for the initial testing of the application. They are as follows:

- Title.
- Author.
- The ISBN, or International Standard Book Number, is a series of ten or thirteen digits that uniquely identify every book published. 

Let's take a look at these generators. 

```erlang
title() ->
    ?LET(S, string(), elements([S, unicode:characters_to_binary(S)])).

author() ->
    ?LET(S, string(), elements([S, unicode:characters_to_binary(S)])).

isbn() ->
    ?LET(ISBN,
         [oneof(["978","979"]),
          ?LET(X, range(0,9999), integer_to_list(X)),
          ?LET(X, range(0,9999), integer_to_list(X)),
          ?LET(X, range(0,999), integer_to_list(X)),
          frequency([{10, range($0,$9)}, {1, "X"}])],
         iolist_to_binary(lists:join("-", ISBN))).
```

Since this is Erlang, and given that the virtual machine has no dedicated string types, both generators will create either multiple lists of characters (`string()`) or binaries of the same text encoded as UTF-8. This will let us check out whether the entire stack can support both types for the `author` and `title` generators. 

For the `isbn` generator, we don’t really care about their text formatting and will assume some other part of the system would test, validate, and normalize them. Instead, we use a more random generator that lets us focus on state transitions for the stateful model.

Now let's test the generators to see if they work.

Take a look at the basic generators required to test the system. 

Writing Generators

Take a look at the basic generators required to test the system.

Foundations of Property-Based Testing

Writing Properties

Thinking in Properties

Custom Generators

Responsible Testing

Properties-Driven Development

Shrinking

Targeted Properties

Stateful Properties

Case Study: Bookstore

State Machine Properties

Conclusion

Writing Generators

Getting started