OCaml DSL for verifiable computation
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jkrauska and bkase Use Stretch (#28)
Resolves #27 and adds some minor context to Readme
Latest commit 1844ba7 Aug 16, 2018



snarky is an OCaml front-end for writing R1CS SNARKs. It is modular over the backend SNARK library, and comes with backends from libsnark.

Disclaimer: This code has not been thoroughly audited and should not be used in production systems.

Getting started

# Build container image 
# (this can easily take ~10m to finish)
docker build -t snarky .

# Start container
docker run -it snarky

Now you should dropped into a shell with snarky installed as an opam library for use in other ocaml projects. You can also use dune to build the examples:

dune b examples/tutorial/tutorial.exe
dune b examples/election/election_main.exe
dune b examples/merkle_update/merkle_update.exe

You can execute them using dune exec.

dune exec examples/tutorial/tutorial.exe

The best place to get started learning how to use the library are the annotated examples.

  • Tutorial: teaches you the basics
  • Election: shows how to use Snarky to verify an election was run honestly.
  • Merkle update: a simple example updating a Merkle tree.


The intention of this library is to allow writing snarks by writing what look like normal programs (whose executions the snarks verify). If you're an experienced functional programmer, the basic idea (simplifying somewhat) is that there is a monad Checked.t so that a value of type 'a Checked.t is an 'a whose computation is certified by the snark. For example, we have a function

mul : var -> var -> (var, _) Checked.t.

Given v1, v2 : var, mul v1 v2 is a variable containing the product of v1 and v2, and the snark will ensure that this is so.

Example: Merkle trees

One computation useful in snarks is verifying membership in a list. This is typically accomplished using authentication paths in Merkle trees. Given a hash entry_hash, an address (i.e., a list of booleans) addr0 and an authentication path (i.e., a list of hashes) path0, we can write a checked computation for computing the implied Merkle root:

  let implied_root entry_hash addr0 path0 =
    let rec go acc addr path =
      let open Let_syntax in
      match addr, path with
      | [], [] -> return acc
      | b :: bs, h :: hs ->
        let%bind l = Hash.if_ b ~then_:h ~else_:acc
        and r = Hash.if_ b ~then_:acc ~else_:h
        let%bind acc' = Hash.hash l r in
        go acc' bs hs
      | _, _ -> failwith "Merkle_tree.Checked.implied_root: address, path length mismatch"
    go entry_hash addr0 path0

The type of this function is

val implied_root : Hash.var -> Boolean.var list -> Hash.var list -> (Hash.var, 'prover_state) Checked.t

The return type (Hash.var, 'prover_state) Checked.t indicates that the function returns a "checked computation" producing a variable containing a hash, and can be run by a prover with an arbitrary state type 'prover_state.

Compare this definition to the following "unchecked" OCaml function (assuming a function hash):

let implied_root_unchecked entry_hash addr0 path0 =
  let rec go acc addr path =
    match addr, path with
    | [], [] -> acc
    | b :: bs, h :: hs ->
      let l = if b then h else acc
      and r = if b then acc else h
      let acc' = hash l r in
      go acc' bs hs
    | _, _ ->
      failwith "Merkle_tree.implied_root_unchecked: address, path length mismatch"
  go entry_hash addr0 path0

The two obviously look very similar, but the first one can be run to generate an R1CS (and also an "auxiliary input") to verify that computation.


Currently, the library uses a free-monad style AST to represent the snark computation. This may change in future versions if the overhead of creating the AST is significant. Most likely it will stick around since the overhead doesn't seem to be too bad and it enables optimizations like eliminating equality constraints.