property-based-testing

Property-based testing for smart contracts uses Echidna or Medusa to discover invariants and generate tests for Solidity and Vyper. It guides you from strategy to test generation to ensure robust contract behavior.

Property-based testing shifts from example-driven tests to pattern-based specifications by defining general properties that hold true across generated inputs. It catches edge cases that fixed examples miss, ensuring more robust software.

Yes, you can apply property-based testing across Python, JavaScript/TypeScript, Rust, Go, Java, Scala, C#, Elixir, Haskell, and Kotlin. It provides structured references and reproducible workflows for generating tests in each language.

You can identify property-based testing opportunities by targeting serialization, normalization, validators, and smart contract invariants. Defining properties for these areas allows you to generate tests that verify fundamental code patterns automatically.

Yes, property-based testing works with Hypothesis and fast-check to apply Property-Driven Development. You can design features with explicit properties, generate tests, and review or refactor existing PBT tests for better coverage.

Limitations of property-based testing include the difficulty of defining accurate properties for complex logic and the potential for long test execution times. It is most effective when you can clearly specify invariants and patterns.