Analyzing Test Case Distribution with PropEr Generators

Writing property-based tests is only half the battle; you must also ensure your custom generators are actually producing the diverse range of data you expect. Without visibility into your test inputs, subtle bugs can easily hide in untested edge cases. This text-only course teaches you how to inspect, analyze, and optimize your test data distribution using the built-in collect function in PropEr. You will learn to gather real-time metrics from your generators, ensuring your Erlang test suites are both robust and comprehensive. What you'll learn: Understand the foundational mechanics of property-based testing and data generation; Implement the collect function within PropEr generators to categorize generated values; Analyze statistical distributions of test inputs to identify gaps in test coverage; Tune custom generators to ensure a balanced mix of typical inputs and complex edge cases; Apply modern testing workflows to verify properties systematically. The course starts with essential concepts of property-based testing and statistical validation before guiding you through the syntax and implementation of data collection functions. You will study practical, written examples and learn how to interpret distribution reports to make data-driven improvements to your test suite. This course is designed for beginners to property-based testing and Erlang developers who want to gain deep visibility into their automated test suites. No prior experience with PropEr statistics is required. Start optimizing your test coverage and write more predictable, high-quality code today.