circom VS circomlibjs

[package] name = "circom-lsp" version = "0.1.0" edition = "2021" authors = ["rubydusa "] license = "GPL-3.0 license" description = "LSP server for Circom" homepage = "https://github.com/rubydusa/circom-lsp" repository = "https://github.com/rubydusa/circom-lsp" [dependencies] tower-lsp = "0.19.0" # lalrpop-util in this specific version required for circom parser to work lalrpop-util = { version = "0.19.9", features = ["lexer"] } circom_parser = { git = "https://github.com/iden3/circom", package = "parser", rev = "ce903c6" } circom_type_checker = { git = "https://github.com/iden3/circom", package = "type_analysis", rev = "ce903c6" } circom_structure = { git = "https://github.com/iden3/circom", package = "program_structure", rev = "ce903c6" } ropey = "1.6.0" tokio = { version = "1.26.0", features = ["rt-multi-thread", "macros", "io-std"] } codespan-reporting = "0.9.0" itertools = "0.10.5" num-traits = "0.2.6" tempfile = "3"

git clone https://github.com/iden3/circom.git cd circom cargo build --release cargo install --path circom

This library uses the compiled circuits generated by the circom compiler.

My current work involves zero-knowledge proofs technology, quite an interesting thing and very similar to writing VHDL code. The language we use for zero-knowledge proofs is circom, compiler here: https://github.com/iden3/circom and the code written in circom is called circuits which is very similar to coding for FPGA platforms.

The advantage of SMT over the general Merkle tree is that it not only allows us to provide an inclusion proof but also an exclusion proof. This means that we can prove that a tree does not contain a value for the given key. Thanks to this, we can prove any operation (insert, delete, update), which will be a very important property of our rollup. Fortunately, Circomlib (and CircomlibJS) includes an SMT implementation, so we do not need to implement this ourselves.

Circomlib has a JS implementation that can be used for this. Let’s install it: