property-based-testing

Property-based testing uncovers hidden edge cases and spec violations by testing general properties across many generated inputs, whereas example-based testing only checks specific hardcoded values. It automatically detects high-value patterns like serialization pairs and pure functions to provide stronger coverage.

To design generators for parsers and validators, define the input domain constraints and select stronger properties like roundtrip, idempotence, invariants, commutativity, or oracle comparisons. This methodical workflow ensures generated inputs exercise the properties before code is implemented or refactored.

Use property-based testing when evaluating transformations, parsers, validators, or pure functions with well-defined contracts. It is appropriate when you need to verify roundtrip, idempotence, invariants, commutativity, and oracle-based properties across generated input domains rather than isolated examples.

To test encode and decode roundtrip properties, invoke the skill to define a roundtrip property and suggest appropriate generators and edge-case examples. This ensures that decoding an encoded value yields the original input across a wide range of generated domains.

Property-based testing is not appropriate when functions lack well-defined contracts or clear invariants. It requires guided selection of property types and careful generator strategy design constraints, making it less suitable for logic without verifiable roundtrip, idempotence, or oracle-based properties.

Yes, property-based testing applies to normalization logic and data-structure operations by verifying invariants and idempotence across generated input domains. It guides the selection of property types and generator strategies to ensure transformations maintain their defined contracts.