compiler-solidity VS stateright

Yul (previously also called JULIA or IULIA) is a simple, low-level intermediate language for the Ethereum Virtual Machine. The Solidity Developers wrote Yul as a compilation target for further optimizations. It features simplistic and functional low-level grammar. It allows developers to get much closer to raw EVM than Solidity, and with that comes the promise of drastically improved gas usage.

YUL compiler. The compiler from YUL intermediate language to zkEVM bytecode.

zkSync's Yul>LLVM compiler is now open source: https://github.com/matter-labs/yul-dev. Solidity > Yul > LLVM (or SyncVM, as they're calling their VM here). Hope to see the zkSync 2.0 testnet go public soon.

stateright - which is meant for distributed state machines and includes a full on model checker

Stateright.

Author seems to be using https://github.com/ailidani/paxi for actual implementation and proof.

I'm more of a python/rust guy. There have been some attempts to make model checkers in rust: https://github.com/stateright/stateright

The issue is that rust is a very large language and it's hard to get it right.

I have a python implementation of raft over here:

https://github.com/adsharma/raft/tree/master/raft/states

That's small enough to be self contained and perhaps run through a model checker some day and transpiled to many statically typed languages.

The issue with TLA+ proofs such as:

https://github.com/fpaxos/raft.tla

is that it's hard to tell if a particular C++ or Rust implementation conforms to the spec.

So how do we check and transpile?

* https://www.philipzucker.com/Modelling_TLA_in_z3py/

Why make memory safety the exception? For example, https://github.com/stateright/stateright implements model checking for distributed systems at the library-level. If you could achieve the same effect with memory safety through the ecosystem, why wouldn't you?

Regarding the last point — correct, Stateright aims to verify both.

It’s important to clarify that this doesn’t provide a proof of correctness, but it can dramatically improve confidence in both the design and implementation compared with fuzz testing, for example. This is done by exhaustively enumerating possible nondeterministic outcomes (e.g. due to message reordering) within specified constraints (e.g. up to S servers and C clients performing X operations…).

Examples:

SD Paxos: https://github.com/stateright/stateright/blob/master/example...

ABD (linearizable register algorithm): https://github.com/stateright/stateright/blob/master/example...

I believe they meant this: https://github.com/stateright/stateright