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Comment by Taikonerd | Hacker News Reader

Using LLMs for formal specs / formal modeling makes a lot of sense to me. If an LLM can do the work of going from informal English-language specs to TLA+ / Dafny / etc, then it can hook into a very mature ecosystem of automated proof tools.

I'm picturing it something like this:

1. Human developer says, "if a user isn't authenticated, they shouldn't be able to place an order."

2. LLM takes this, and its knowledge of the codebase, and turns it into a formal spec -- like, "there is no code path where User.is_authenticated is false and Orders.place() is called."

3. Existing code analysis tools can confirm or find a counterexample.

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A fascinating thought. But then who verifies that the TLA+ specification does indeed match the human specification?

I’m guessing using an LLM as a translator narrows the gap, and better LLMs will make it narrower eventually, but is there a way to quantify this? For example how would it compare to a human translating the spec into TLA+?

maybe run it through few other LLMs depending on how much confidence you need - o3 pro, gemini 2.5 pro, claude 3.7, grok 3, etc..

Then you need to be able to formally prove the equivalence of various TLA+ programs (maybe that's a solved problem?)

No idea about SOTA but naively it doesn't seem like a very difficult problem:

- Ensure all TLA+ specs produced have the same inputs/outputs (domains, mostly a prompting problem and can solved with retries)

- That all TLA+ produce the same outputs for the same inputs (making them functionally equivalent in practice, might be computationally intensive)

Of course that assumes your input domains are countable but it's probably okay to sample from large ranges for a certain "level" of equivalence.

EDIT: Not sure how that will work with non-determinism though.

I didn't mean generate separate TLA programs. Rather, other LLMs review and comment on whether this TLA program satisfies the user's specification.

A fair question! I'd say it's not that different from using an LLM to write regular code: who verifies that the code the LLM wrote is indeed what you meant?

The usual way to check whether a definition is correct is to prove properties about it that you think should hold. TLA+ has good support for this, both with model checking as well as simple proofs.

It makes a lot of sense only for graphics card sales people. For everyone else with a working neuron the sole idea is utter nonsense.

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