formal-spec-generator

To generate formal specifications for concurrent system properties, route your requests to the TLA+ formalism, which handles concurrency properties like race condition absence. The skill prioritizes simpler model checking methods over complex theorem proving.

For sequential code correctness in Python or C/C++, use Dafny specification generation. The skill intelligently routes sequential code verification requests to specialized tools based on input type and desired output formalism.

Use Lean for complex theorem proving, whereas Dafny suits sequential code correctness and TLA+ targets concurrent systems. The skill prioritizes simpler verification methods like model checking before escalating to complex theorem proving.

Yes, you can formalize natural language requirements. The skill supports routing natural language requirement formalization requests across Dafny, TLA+, Lean, and SMV formalisms based on your specific verification goals.

Yes, the formal specification generator supports invariant inference. It dispatches invariant inference requests to specialized tools, selecting the appropriate formalism like SMV or Lean based on your specific verification objectives.

Automated formal specification generation prioritizes simpler verification methods like model checking before complex theorem proving. Users may encounter limitations when requiring advanced Lean theorem proofs if simpler Dafny or TLA+ methods are insufficient.