Skip to content
All Skills

Property Based Testing

Property-based testing with fast-check (TypeScript/JavaScript) and Hypothesis (Python). Generate test cases automatically, find edge cases, and test mathematical properties. Use when user mentions property-based testing, fast-check, Hypothesis, generating test data, QuickCheck-style testing, or finding edge cases automatically.

Software Engineering|v1|Updated 7/14/2026|GitHub source
MCP get_skill({ skillId: "property-based-testing-b000312a" })

Use this skill with your agent

Create a free account and connect via MCP

Get Started Free
# Property-Based Testing

Expert knowledge for property-based testing - automatically generating test cases to verify code properties rather than testing specific examples.

## Core Expertise

**Property-Based Testing Concept**
- **Traditional testing**: Test specific examples
- **Property-based testing**: Test properties that should hold for all inputs
- **Generators**: Automatically create diverse test inputs
- **Shrinking**: Minimize failing cases to simplest example
- **Coverage**: Explore edge cases humans might miss

**When to Use Property-Based Testing**
- Mathematical operations (commutative, associative properties)
- Encoders/decoders (roundtrip properties)
- Parsers and serializers
- Data transformations
- API contracts
- Invariants and constraints

## TypeScript/JavaScript (fast-check)

### Installation

```bash
# Using Bun
bun add -d fast-check

# Using npm
npm install -D fast-check
```

### Basic Example

```typescript
import { test } from 'vitest'
import * as fc from 'fast-check'

// Traditional example-based test
test('reverse twice returns original', () => {
  expect(reverse(reverse([1, 2, 3]))).toEqual([1, 2, 3])
})

// Property-based test
test('reverse twice returns original - property based', () => {
  fc.assert(
    fc.property(
      fc.array(fc.integer()), // Generate random arrays of integers
      (arr) => {
        expect(reverse(reverse(arr))).toEqual(arr)
      }
    )
  )
})
// fast-check automatically generates 100s of test cases!
```

### Built-in Generators

```typescript
import * as fc from 'fast-check'

// Numbers
fc.integer()                          // Any integer
fc.integer({ min: 0, max: 100 })      // Range
fc.nat()                              // Natural numbers (≥ 0)
fc.float()                            // Floating-point
fc.double()                           // Double precision

// Strings
fc.string()                           // Any string
fc.string({ minLength: 1, maxLength: 10 })
fc.hexaString()                       // Hex strings
fc.asciiString()                      // ASCII only
fc.unicodeString()                    // Unicode
fc.emailAddress()                     // Email format

// Arrays and Objects
fc.array(fc.integer())                // Array of integers
fc.array(fc.string(), { minLength: 1, maxLength: 5 })
fc.set(fc.integer())                  // Unique values
fc.record({                           // Objects
  name: fc.string(),
  age: fc.nat(),
})

// Booleans and Constants
fc.boolean()
fc.constant('value')
fc.constantFrom('a', 'b', 'c')        // Pick from options

// Dates
fc.date()
fc.date({ min: new Date('2020-01-01') })

// Complex Types
fc.tuple(fc.string(), fc.integer())   // Fixed-size tuple
fc.oneof(fc.string(), fc.integer())   // Union type
fc.option(fc.string())                // string | null
```

### Custom Generators

```typescript
// Generate user objects
const userArbitrary = fc.record({
  id: fc.nat(),
  name: fc.string({ minLength: 1, maxLength: 50 }),
  email: fc.emailAddress(),
  age: fc.integer({ min: 18, max: 120 }),
  roles: fc.array(fc.constantFrom('admin', 'user', 'guest'), {
    minLength: 1,
    maxLength: 3,
  }),
})

test('user validation properties', () => {
  fc.assert(
    fc.property(userArbitrary, (user) => {
      const validated = validateUser(user)
      expect(validated.age).toBeGreaterThanOrEqual(18)
      expect(validated.name.length).toBeGreaterThan(0)
      expect(validated.roles.length).toBeGreaterThan(0)
    })
  )
})

// Generate using map
const positiveNumberArbitrary = fc.nat().map((n) => n + 1)

// Generate using chain (dependent values)
const emailAndDomainArbitrary = fc.string().chain((domain) =>
  fc.record({
    email: fc.constant(`user@${domain}.com`),
    domain: fc.constant(domain),
  })
)
```

### Common Properties to Test

#### Roundtrip Property (Encode/Decode)

```typescript
test('JSON serialization roundtrip', () => {
  fc.assert(
    fc.property(
      fc.record({
        name: fc.string(),
        age: fc.nat(),
        tags: fc.array(fc.string()),
      }),
      (obj) => {
        const serialized = JSON.stringify(obj)
        const deserialized = JSON.parse(serialized)
        expect(deserialized).toEqual(obj)
      }
    )
  )
})
```

#### Idempotence (f(f(x)) = f(x))

```typescript
test('sort is idempotent', () => {
  fc.assert(
    fc.property(fc.array(fc.integer()), (arr) => {
      const sorted = sort(arr)
      const doubleSorted = sort(sorted)
      expect(doubleSorted).toEqual(sorted)
    })
  )
})
```

#### Commutativity (f(a, b) = f(b, a))

```typescript
test('addition is commutative', () => {
  fc.assert(
    fc.property(fc.integer(), fc.integer(), (a, b) => {
      expect(add(a, b)).toBe(add(b, a))
    })
  )
})
```

#### Associativity ((a + b) + c = a + (b + c))

```typescript
test('addition is associative', () => {
  fc.assert(
    fc.property(fc.integer(), fc.integer(), fc.integer(), (a, b, c) => {
      expect(add(add(a, b), c)).toBe(add(a, add(b, c)))
    })
  )
})
```

#### Identity (f(x, identity) = x)

```typescript
test('multiplication identity', () => {
  fc.assert(
    fc.property(fc.integer(), (n) => {
      expect(multiply(n, 1)).toBe(n)
    })
  )
})
```

#### Inverse (f(g(x)) = x)

```typescript
test('encryption/decryption inverse', () => {
  fc.assert(
    fc.property(fc.string(), fc.string(), (plaintext, key) => {
      const encrypted = encrypt(plaintext, key)
      const decrypted = decrypt(encrypted, key)
      expect(decrypted).toBe(plaintext)
    })
  )
})
```

### Shrinking (Simplifying Failing Cases)

```typescript
// When a property fails, fast-check automatically shrinks
// the input to the minimal failing case

test('finds minimal failing case', () => {
  fc.assert(
    fc.property(fc.array(fc.integer()), (arr) => {
      // This will fail for arrays containing 42
      expect(arr).not.toContain(42)
    })
  )
})

// Output:
// Property failed after 1 tests
// Shrunk 5 time(s)
// Counterexample: [[42]]  ← Minimal failing case!
```

### Configuration

```typescript
test('configured property test', () => {
  fc.assert(
    fc.property(fc.array(fc.integer()), (arr) => {
      expect(sort(arr)).toBeSorted()
    }),
    {
      numRuns: 1000,      // Run 1000 tests (default: 100)
      seed: 42,           // Reproducible tests
      endOnFailure: true, // Stop after first failure
      verbose: true,      // Show all generated values
    }
  )
})
```

### Preconditions (Filtering)

```typescript
test('division properties for non-zero divisors', () => {
  fc.assert(
    fc.property(fc.integer(), fc.integer(), (a, b) => {
      fc.pre(b !== 0) // Skip cases where b is 0

      const result = divide(a, b)
      expect(multiply(result, b)).toBeCloseTo(a)
    })
  )
})
```

## Python (Hypothesis)

### Installation

```bash
# Using uv
uv add --dev hypothesis

# Using pip
pip install hypothesis
```

### Basic Example

```python
from hypothesis import given, strategies as st
import pytest

# Traditional example-based test
def test_reverse_twice_example():
    assert reverse(reverse([1, 2, 3])) == [1, 2, 3]

# Property-based test
@given(st.lists(st.integers()))
def test_reverse_twice_property(arr):
    assert reverse(reverse(arr)) == arr
    # Hypothesis automatically generates 100s of test cases!
```

### Built-in Strategies

```python
from hypothesis import strategies as st

# Numbers
st.integers()                          # Any integer
st.integers(min_value=0, max_value=100)
st.floats()                            # Floating-point
st.floats(min_value=0.0, max_value=1.0, allow_nan=False)
st.decimals()                          # Decimal precision

# Strings
st.text()                              # Any string
st.text(min_size=1, max_size=10)
st.text(alphabet='abc')                # Limited alphabet
st.binary()                            # Bytes

# Collections
st.lists(st.integers())                # List of integers
st.lists(st.text(), min_size=1, max_size=5)
st.sets(st.integers())                 # Unique values
st.dictionaries(keys=st.text(), values=st.integers())

# Booleans and Constants
st.booleans()
st.just('value')                       # Constant
st.sampled_from(['a', 'b', 'c'])      # Pick from options

# Dates and Times
st.dates()
st.datetimes()
st.times()
st.timedeltas()

# Complex Types
st.tuples(st.text(), st.integers())   # Fixed-size tuple
st.one_of(st.text(), st.integers())   # Union type
```

### Custom Strategies

```python
from hypothesis import strategies as st
from dataclasses import dataclass

@dataclass
class User:
    id: int
    name: str
    email: str
    age: int

# Strategy for generating users
users = st.builds(
    User,
    id=st.integers(min_value=1),
    name=st.text(min_size=1, max_size=50),
    email=st.emails(),
    age=st.integers(min_value=18, max_value=120),
)

@given(users)
def test_user_validation(user):
    validated = validate_user(user)
    assert validated.age >= 18
    assert len(validated.name) > 0
```

```python
# Using map
positive_numbers = st.integers(min_value=0).map(lambda n: n + 1)

# Using flatmap (dependent values)
@st.composite
def email_and_domain(draw):
    domain = draw(st.text(min_size=1))
    return {
        'email': f'user@{domain}.com',
        'domain': domain,
    }
```

### Common Properties to Test

#### Roundtrip Property

```python
import json
from hypothesis import given, strategies as st

@given(st.dictionaries(
    keys=st.text(),
    values=st.one_of(st.integers(), st.text(), st.booleans())
))
def test_json_roundtrip(obj):
    serialized = json.dumps(obj)
    deserialized = json.loads(serialized)
    assert deserialized == obj
```

#### Idempotence

```python
@given(st.lists(st.integers()))
def test_sort_idempotent(arr):
    sorted_once = sorted(arr)
    sorted_twice = sorted(sorted_once)
    assert sorted_once == sorted_twice
```

#### Commutativity

```python
@given(st.integers(), st.integers())
def test_addition_commutative(a, b):
    assert add(a, b) == add(b, a)
```

#### Associativity

```python
@given(st.integers(), st.integers(), st.integers())
def test_addition_associative(a, b, c):
    assert add(add(a, b), c) == add(a, add(b, c))
```

#### Identity

```python
@given(st.integers())
def test_multiplication_identity(n):
    assert multiply(n, 1) == n
```

#### Inverse

```python
@given(st.text(), st.text(min_size=1))
def test_encryption_inverse(plaintext, key):
    encrypted = encrypt(plaintext, key)
    decrypted = decrypt(encrypted, key)
    assert decrypted == plaintext
```

### Shrinking (Simplifying Failing Cases)

```python
from hypothesis import given, strategies as st

@given(st.lists(st.integers()))
def test_finds_minimal_failing_case(arr):
    # This will fail for arrays containing 42
    assert 42 not in arr

# Output:
# Falsifying example: test_finds_minimal_failing_case(
#     arr=[42]  ← Minimal failing case!
# )
```

### Configuration and Settings

```python
from hypothesis import given, settings, strategies as st

@settings(max_examples=1000, deadline=None)
@given(st.lists(st.integers()))
def test_with_custom_settings(arr):
    assert sort(arr) == sorted(arr)

# Global settings
from hypothesis import settings, Verbosity

settings.register_profile("ci", max_examples=1000, verbosity=Verbosity.verbose)
settings.register_profile("dev", max_examples=100)
settings.load_profile("dev")
```

### Assumptions (Preconditions)

```python
from hypothesis import given, assume, strategies as st

@given(st.integers(), st.integers())
def test_division_properties(a, b):
    assume(b != 0)  # Skip cases where b is 0

    result = divide(a, b)
    assert abs(multiply(result, b) - a) < 0.0001
```

### Stateful Testing

```python
from hypothesis.stateful import RuleBasedStateMachine, rule, invariant
from hypothesis import strategies as st

class ShoppingCartMachine(RuleBasedStateMachine):
    def __init__(self):
        super().__init__()
        self.cart = ShoppingCart()
        self.items = []

    @rule(item=st.text(min_size=1), price=st.floats(min_value=0.01, max_value=1000))
    def add_item(self, item, price):
        self.cart.add(item, price)
        self.items.append((item, price))

    @rule()
    def clear_cart(self):
        self.cart.clear()
        self.items = []

    @invariant()
    def total_matches_items(self):
        expected_total = sum(price for _, price in self.items)
        assert abs(self.cart.total() - expected_total) < 0.01

# Run stateful test
TestCart = ShoppingCartMachine.TestCase
```

## Real-World Examples

### TypeScript: URL Parser

```typescript
import * as fc from 'fast-check'

test('URL parsing roundtrip', () => {
  fc.assert(
    fc.property(
      fc.webUrl(), // Built-in URL generator
      (url) => {
        const parsed = parseURL(url)
        const reconstructed = buildURL(parsed)
        expect(normalizeURL(reconstructed)).toBe(normalizeURL(url))
      }
    )
  )
})
```

### Python: Data Validation

```python
from hypothesis import given, strategies as st
from pydantic import BaseModel, ValidationError

class Product(BaseModel):
    name: str
    price: float
    quantity: int

@given(st.builds(
    Product,
    name=st.text(min_size=1),
    price=st.floats(min_value=0.01, max_value=10000),
    quantity=st.integers(min_value=0, max_value=1000),
))
def test_product_validation_accepts_valid_data(product):
    # Should not raise
    validated = Product(**product.dict())
    assert validated.price > 0
    assert validated.quantity >= 0
```

### TypeScript: List Operations

```typescript
test('filter and map compose correctly', () => {
  fc.assert(
    fc.property(
      fc.array(fc.integer()),
      fc.func(fc.boolean()),
      fc.func(fc.integer()),
      (arr, predicate, transform) => {
        const result1 = arr.filter(predicate).map(transform)
        const result2 = arr.map(transform).filter((_, i) =>
          predicate(arr[i])
        )
        // Order might differ but length should match
        expect(result1.length).toBe(result2.length)
      }
    )
  )
})
```

### Python: Cache Behavior

```python
from hypothesis import given, strategies as st

@given(st.text(), st.integers())
def test_cache_returns_same_value(key, value):
    cache = Cache()

    # First set
    cache.set(key, value)
    result1 = cache.get(key)

    # Second get should return same value
    result2 = cache.get(key)

    assert result1 == value
    assert result2 == value
```

## Best Practices

**Start with Properties**
- Identify mathematical properties (commutative, associative)
- Look for roundtrip properties (encode/decode)
- Test invariants (things that should always be true)
- Verify contracts and postconditions

**Complement Example-Based Tests**
```typescript
// Use both approaches
test('addition examples', () => {
  expect(add(2, 3)).toBe(5)
  expect(add(-1, 1)).toBe(0)
})

test('addition properties', () => {
  fc.assert(
    fc.property(fc.integer(), fc.integer(), (a, b) => {
      expect(add(a, b)).toBe(add(b, a)) // Commutative
      expect(add(a, 0)).toBe(a)          // Identity
    })
  )
})
```

**Shrinking is Your Friend**
- Don't ignore shrunk counterexamples
- Minimal failing cases reveal root causes
- Shrinking finds edge cases you'd never write by hand

**Performance Considerations**
```typescript
// Limit expensive tests
fc.assert(
  fc.property(fc.array(fc.integer()), (arr) => {
    expensiveOperation(arr)
  }),
  { numRuns: 50 } // Reduce from default 100
)
```

**Reproducibility**
```python
# Set seed for reproducible failures
@settings(derandomize=True)
@given(st.lists(st.integers()))
def test_reproducible(arr):
    assert process(arr) is not None
```

## Common Pitfalls

**Overly Permissive Assertions**
```typescript
// ❌ BAD: Too weak
fc.assert(
  fc.property(fc.array(fc.integer()), (arr) => {
    expect(sort(arr)).toBeDefined() // Passes even if sort is broken!
  })
)

// ✅ GOOD: Specific properties
fc.assert(
  fc.property(fc.array(fc.integer()), (arr) => {
    const sorted = sort(arr)
    // Check actual properties
    for (let i = 1; i < sorted.length; i++) {
      expect(sorted[i]).toBeGreaterThanOrEqual(sorted[i - 1])
    }
  })
)
```

**Too Many Assumptions**
```python
# ❌ BAD: Filters out too many cases
@given(st.integers(), st.integers())
def test_slow(a, b):
    assume(a > 100)
    assume(a < 110)
    assume(b > 200)
    assume(b < 210)
    # Better to use specific strategy!

# ✅ GOOD: Generate what you need
@given(st.integers(min_value=101, max_value=109),
       st.integers(min_value=201, max_value=209))
def test_fast(a, b):
    # No filtering needed
```

**Testing Implementation, Not Properties**
```typescript
// ❌ BAD: Tests implementation
fc.assert(
  fc.property(fc.array(fc.integer()), (arr) => {
    const spy = vi.spyOn(Math, 'max')
    sort(arr)
    expect(spy).toHaveBeenCalled() // Testing how it's implemented
  })
)

// ✅ GOOD: Tests properties
fc.assert(
  fc.property(fc.array(fc.integer()), (arr) => {
    const sorted = sort(arr)
    // Test what it does, not how
    expect(sorted.length).toBe(arr.length)
    expect(new Set(sorted)).toEqual(new Set(arr))
  })
)
```

## CI/CD Integration

### TypeScript

```json
{
  "scripts": {
    "test": "vitest",
    "test:property": "vitest --grep 'property'",
    "test:ci": "vitest --run --coverage"
  }
}
```

### Python

```yaml
# .github/workflows/test.yml
name: Tests

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v1
      - run: uv sync
      - run: uv run pytest --hypothesis-show-statistics
```

## Troubleshooting

**Tests taking too long**
```typescript
// Reduce number of runs
fc.assert(property, { numRuns: 50 })
```

```python
@settings(max_examples=50)
@given(...)
```

**Hard to find failing case**
```typescript
// Increase attempts
fc.assert(property, { numRuns: 10000 })
```

**Flaky property tests**
```python
# Use seed for reproducibility
@settings(derandomize=True)
```

**Too many filtered cases**
```
Hypothesis: Unable to satisfy assumptions
```
→ Use more specific generators instead of `assume()`

## See Also

- `vitest-testing` - Unit testing framework
- `python-testing` - Python pytest testing
- `test-quality-analysis` - Detecting test smells
- `mutation-testing` - Validate test effectiveness

## References

- fast-check: https://fast-check.dev/
- Hypothesis: https://hypothesis.readthedocs.io/
- Property-Based Testing: https://fsharpforfunandprofit.com/posts/property-based-testing/
#broad-capability#creative#testing

Related Skills

More skills in Software Engineering

Accessibility Standards

Comprehensive web accessibility standards based on WCAG 2.2 AA, with 38+ anti-patterns, legal enforcement context (EAA, ADA Title II), WAI-ARIA patterns, and framework-specific fixes for modern web frameworks and libraries.

#github-copilot#accessibilityMIT

Accord

Authoring unified specification packages across Business/Development/Design teams via staged elaboration (L0 Vision → L1 Requirements → L2 Team Detail → L3 Acceptance Criteria). No code. Use when authoring cross-team specs, building L0-L3 packages, or aligning Biz/Dev/Design on a single source of truth.

#broad-capability#developmentMIT

Acquire Codebase Knowledge

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

#github-copilot#documentationMIT

Acreadiness Assess

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

#github-copilot#planningMIT

Acreadiness Generate Instructions

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

#github-copilot#skillMIT

Acreadiness Policy

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

#github-copilot#planningMIT