Aj Geddes Useful AI Prompts Property Based Testing

Property-Based Testing

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Property-based testing verifies that code satisfies general properties or invariants for a wide range of automatically generated inputs, rather than testing specific examples. This approach finds edge cases and bugs that example-based tests often miss.

When to Use

• Testing algorithms with mathematical properties
• Verifying invariants that should always hold
• Finding edge cases automatically
• Testing parsers and serializers (round-trip properties)
• Validating data transformations
• Testing sorting, searching, and data structure operations
• Discovering unexpected input combinations

Quick Start

Minimal working example:

# test_string_operations.py
import pytest
from hypothesis import given, strategies as st, assume, example

def reverse_string(s: str) -> str:
    """Reverse a string."""
    return s[::-1]

class TestStringOperations:
    @given(st.text())
    def test_reverse_twice_returns_original(self, s):
        """Property: Reversing twice returns the original string."""
        assert reverse_string(reverse_string(s)) == s

    @given(st.text())
    def test_reverse_length_unchanged(self, s):
        """Property: Reverse doesn't change length."""
        assert len(reverse_string(s)) == len(s)

    @given(st.text(min_size=1))
    def test_reverse_first_becomes_last(self, s):
        """Property: First char becomes last after reverse."""
        reversed_s = reverse_string(s)
        assert s[0] == reversed_s[-1]
        assert s[-1] == reversed_s[0]
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Best Practices

✅ DO

• Focus on general properties, not specific cases
• Test mathematical properties (commutativity, associativity)
• Verify round-trip encoding/decoding
• Use shrinking to find minimal failing cases
• Combine with example-based tests for known edge cases
• Test invariants that should always hold
• Generate realistic input distributions

❌ DON'T

• Test properties that are tautologies
• Over-constrain input generation
• Ignore shrunk test failures
• Replace all example tests with properties
• Test implementation details
• Generate invalid inputs without constraints
• Forget to handle edge cases in generators

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