> For the complete documentation index, see [llms.txt](https://docs.coveragelabs.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coveragelabs.io/services/fuzzing-campaign/invariant-development.md).

# Invariant Development

## Invariant Identification

During this phase we collaborate closely with your engineering team to identify both system-level invariants (e.g "The sum of user balances must always equal the total supply") and function-level invariants (e.g "This function must never decrease the protocol's balance"). These invariants are documented in clear English, accompanied by preconditions and bounds to ensure they reflect realistic scenarios. Our team conducts structured brainstorming sessions with your engineering team to identify implicit protocol rules.

## Iterative Improvement

We refine invariants based on short fuzzing campaign results, tightening preconditions and arithmetic bounds to ensure all code paths are tested and eliminate false positives. The goal is to produce a suite that is both rigorous and maintainable, while capable of evolving alongside your codebase. 


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