What is the main benefit of using this PBT workflow?

It helps identify critical edge cases that manual unit tests often miss by automatically generating thousands of randomized inputs based on high-level properties of your code.

Does this skill support the official MoonBit QuickCheck library?

Yes, it is specifically designed for moonbitlang/quickcheck and includes a migration guide for users moving from older libraries like Aletheia.

How does the Pattern Decision Tree assist in testing?

It asks targeted questions about your function's characteristics (like whether an inverse exists) to help you choose the most effective testing strategy, such as Idempotent, Oracle, or Round-Trip.

Can I implement PBT for custom data types?

Absolutely. The skill provides detailed instructions and implementation patterns for the Arbitrary and Shrink traits, allowing you to test complex, domain-specific types.

MoonBit PBT Workflow Guide

Name: MoonBit PBT Workflow Guide
Author: f4ah6o

byf4ah6o

Security & Testing

Automates the implementation and optimization of Property-Based Testing in MoonBit projects using the QuickCheck framework.

About

This skill provides a structured framework for introducing, updating, and maintaining Property-Based Testing (PBT) in MoonBit repositories. It streamlines the transition from traditional unit testing to robust property-based validation by offering a pattern decision tree, guidance on generator design, and implementation strategies for custom types. Whether you are verifying complex algorithms via Oracle testing or ensuring data integrity through Round-Trip patterns, this skill ensures your MoonBit code remains resilient and edge-case-proof.

Key Features

Automated migration path from the legacy Aletheia testing library
Pattern decision tree for selecting Round-Trip, Oracle, or Invariant tests
0 GitHub stars
Advanced generator design with weighted distribution and frequency control
Standardized CI/CD workflow for branch-based PBT development
Custom Shrink trait implementation for minimal counterexample discovery

Use Cases

Verifying data serialization/deserialization logic through Round-Trip testing
Stress-testing complex stateful systems using automated property generation
Migrating existing test suites to the official moonbitlang/quickcheck library

About

Key Features

Automated migration path from the legacy Aletheia testing library
Pattern decision tree for selecting Round-Trip, Oracle, or Invariant tests
0 GitHub stars
Advanced generator design with weighted distribution and frequency control
Standardized CI/CD workflow for branch-based PBT development
Custom Shrink trait implementation for minimal counterexample discovery

Use Cases

Verifying data serialization/deserialization logic through Round-Trip testing
Stress-testing complex stateful systems using automated property generation
Migrating existing test suites to the official moonbitlang/quickcheck library