/property-based-testing

name: property-based-testing
description: Use when writing tests for serialization, validation, normalization, or pure functions - provides property catalog, pattern detection, and library reference for property-based testing
user-invocable: false

Property-Based Testing

Overview

Property-based testing (PBT) generates random inputs and verifies that properties hold for all of them. Instead of testing specific examples, you test invariants.

**When PBT beats example-based tests:**

• Serialization pairs (encode/decode)
• Pure functions with clear contracts
• Validators and normalizers
• Data structure operations

Property Catalog

| Property | Formula | When to Use | |----------|---------|-------------| | **Roundtrip** | `decode(encode(x)) == x` | Serialization, conversion pairs | | **Idempotence** | `f(f(x)) == f(x)` | Normalization, formatting, sorting | | **Invariant** | Property holds before/after | Any transformation | | **Commutativity** | `f(a, b) == f(b, a)` | Binary/set operations | | **Associativity** | `f(f(a,b), c) == f(a, f(b,c))` | Combining operations | | **Identity** | `f(x, identity) == x` | Operations with neutral element | | **Inverse** | `f(g(x)) == x` | encrypt/decrypt, compress/decompress | | **Oracle** | `new_impl(x) == reference(x)` | Optimization, refactoring | | **Easy to Verify** | `is_sorted(sort(x))` | Complex algorithms | | **No Exception** | No crash on valid input | Baseline (weakest) |

**Strength hierarchy** (weakest to strongest):

No Exception -> Type Preservation -> Invariant -> Idempotence -> Roundtrip

Always aim for the strongest property that applies.

Pattern Detection

**Use PBT when you see:**

| Pattern | Property | Priority | |---------|----------|----------| | `encode`/`decode`, `serialize`/`deserialize` | Roundtrip | HIGH | | `toJSON`/`fromJSON`, `pack`/`unpack` | Roundtrip | HIGH | | Pure functions with clear contracts | Multiple | HIGH | | `normalize`, `sanitize`, `canonicalize` | Idempotence | MEDIUM | | `is_valid`, `validate` with normalizers | Valid after normalize | MEDIUM | | Sorting, ordering, comparators | Idempotence + ordering | MEDIUM | | Custom collections (add/remove/get) | Invariants | MEDIUM | | Builder/factory patterns | Output invariants | LOW |

When NOT to Use

• Simple CRUD without transformation logic
• UI/presentation logic
• Integration tests requiring complex external setup
• Code with side effects that cannot be isolated
• Prototyping where requirements are fluid
• Tests where specific examples suffice and edge cases are understood

Library Quick Reference

| Language | Library | Import | |----------|---------|--------| | Python | Hypothesis | `from hypothesis import given, strategies as st` | | TypeScript/JS | fast-check | `import fc from 'fast-check'` | | Rust | proptest | `use proptest::prelude::*` | | Go | rapid | `import "pgregory.net/rapid"` | | Java | jqwik | `@Property` annotations | | Haskell | QuickCheck | `import Test.QuickCheck` |

**For library-specific syntax and patterns:** Use `@ed3d-research-agents:internet-researcher` to get current documentation.

Input Strategy Best Practices

1. **Constrain early:** Build constraints INTO the strategy, not via `assume()`

   # GOOD
   st.integers(min_value=1, max_value=100)

   # BAD - high rejection rate
   st.integers().filter(lambda x: 1 <= x <= 100)

2. **Size limits:** Prevent slow tests

   st.lists(st.integers(), max_size=100)
   st.text(max_size=1000)

3. **Realistic data:** Match real-world constraints

   st.integers(min_value=0, max_value=150)  # Real ages, not arbitrary ints

4. **Reuse strategies:** Define once, use across tests

   valid_users = st.builds(User, ...)

   @given(valid_users)
   def test_one(user): ...

   @given(valid_users)
   def test_two(user): ...

Settings Guide

# Development (fast feedback)
@settings(max_examples=10)

# CI (thorough)
@settings(max_examples=200)

# Nightly/Release (exhaustive)
@settings(max_examples=1000, deadline=None)

Quality Checklist

Before committing PBT tests:

• [ ] Not tautological (assertion doesn't compare same expression)
• [ ] Strong assertion (not just "no crash")
• [ ] Not vacuous (inputs not over-filtered by `assume()`)
• [ ] Edge cases covered with explicit examples (`@example`)
• [ ] No reimplementation of function logic in assertion
• [ ] Strategy constraints are realistic
• [ ] Settings appropriate for context

Red Flags

• **Tautological:** `assert sorted(xs) == sorted(xs)` tests nothing
• **Only "no crash":** Always look for stronger properties
• **Vacuous:** Multiple `assume()` calls filter out most inputs
• **Reimplementation:** `assert add(a, b) == a + b` if that's how add is implemented
• **Missing edge cases:** No `@example([])`, `@example([1])` decorators
• **Overly constrained:** Many `assume()` calls means redesign the strategy

Common Mistakes

| Mistake | Fix | |---------|-----| | Testing mock behavior | Test real behavior | | Reimplementing function in test | Use algebraic properties | | Filtering with assume() | Build constraints into strategy | | No edge case examples | Add @example decorators | | One property only | Add multiple properties (length, ordering, etc.) |