Property-based testing – Introducing automated edge-case testing for Plutus smart contracts, enhancing reliability and security 1/ Ever worried about hidden bugs lurking in smart contracts, especially those hard-to-find 'edge cases'? 🧐 Currently, the Cardano ecosystem could benefit from specific property-based testing (PBT) tools for smart contracts. The lack of these tools means smart contracts are more exposed to undetected issues and potential security flaws, which can pose significant risks.
2/ But there's a proposal to change that! 👇 The Plinth PBT tool is designed to perform property-based testing on Plinth smart contracts. By automatically generating a wide range of inputs and actions to test against the specified properties of a contract, it ensures that the contract behaves as expected.
3/ This tool helps developers identify edge cases, validate assumptions, improve contract robustness, and check against known vulnerabilities. It integrates seamlessly into the Plinth development workflow, enabling more rigorous and automated testing, ultimately enhancing the reliability and security of Plinth scripts. It includes benefits such as: ✅Reduced financial losses: prevents costly bugs and exploits ✅Increased confidence: builds trust in Cardano’s smart contracts ✅Enhanced code quality: boosts contract robustness.
4/ PBT also brings enhanced code quality by boosting contract robustness and bridging a critical gap in Cardano's security infrastructure. It integrates seamlessly into the Plutus development workflow.
5/ Stay tuned for updates and learn more about Cardano’s 2025 vision and roadmap:
6/ If you enjoyed reading this thread, check out yesterday’s post about automatic formal verification, which allows for mathematically proving DApp correctness with the click of a button.
Input | Output
Input | Output24.6.2025
Automatic formal verification – Mathematically proving DApp correctness with the click of a button. Cardano DApps currently lack accessible formal verification tools. This gap exposes them to security risks and potential economic loss, as current testing often misses vulnerabilities or requires deep expertise, high costs, and time. 1/5
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