Generates pragmatic verification artifacts like contracts and property-based tests for Python and Go code.
This skill bridges the gap between basic coding and full formal verification by automatically generating design-by-contract assertions, property-based tests, and runtime invariant checks. It helps developers ensure code correctness for complex logic—such as concurrency, floating-point math, or CRUD operations—without the heavy overhead of formal methods like Dafny, providing a scalable and pragmatic approach to software reliability and bug prevention.
Key Features
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02Creates property-based tests using industry-standard libraries like Hypothesis and rapid.
03Automatic extraction of pre/postconditions and invariants from code or natural language.
04Generates Design-by-Contract assertions for Python and Go environments.
05Implements runtime invariant checks with optional debug-mode gating for production safety.
06Provides verification gap analysis to identify when full formal verification is required.
Use Cases
01Creating robust documentation through formal-style contracts and invariants that stay in sync with the code.
02Adding correctness guarantees to complex algorithms or data transformations where manual testing is insufficient.
03Validating edge cases in concurrency or floating-point calculations that are difficult to prove formally.
