fix build (#68)

* fix build

* address clippy, switch to stable

* fix build

Author: srinathsetty

.github/workflows/rust.yml

@@ -7,12 +7,12 @@ on:
     branches: [ master ]
 
 jobs:
-  build_nightly:
+  build:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v2
     - name: Install
-      run: rustup default nightly
+      run: rustup default stable 
     - name: Install rustfmt Components
       run: rustup component add rustfmt
     - name: Install clippy
@@ -28,13 +28,15 @@ jobs:
     - name: Check clippy warnings
       run: cargo clippy --all-targets --all-features -- -D warnings
 
-  build_nightly_wasm:
+  
+
+  build_wasm:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v2
 
     - name: Install
-      run: rustup default nightly
+      run: rustup default stable 
 
     - name: Build without std
       run: cargo build --no-default-features --verbose
@@ -53,14 +55,3 @@ jobs:
 
     - name: Build for target wasm-wasi
       run: RUSTFLAGS="" cargo build --target=wasm32-wasi --no-default-features --verbose
-    
-    - name: Patch Cargo.toml for wasm-bindgen
-      run: |
-        echo "[dependencies.getrandom]" >> Cargo.toml
-        echo "version = \"0.1\"" >> Cargo.toml
-        echo "default-features = false" >> Cargo.toml
-        echo "features = [\"wasm-bindgen\"]" >> Cargo.toml
-
-    - name: Build for target wasm32-unknown-unknown
-      run: RUSTFLAGS="" cargo build --target=wasm32-unknown-unknown --no-default-features --verbose
-    

Cargo.toml

@@ -14,17 +14,18 @@ keywords = ["zkSNARKs", "cryptography", "proofs"]
 curve25519-dalek = { version = "4.1.1", features = [
     "serde",
     "alloc",
+    "rand_core",
 ], default-features = false }
 merlin = { version = "3.0.0", default-features = false }
-rand = { version = "0.7.3", features = ["getrandom"], default-features = false }
+rand = "0.8"
+rand_core = { version = "0.6", default-features = false, features = ["getrandom"] }
 digest = { version = "0.8.1", default-features = false }
 sha3 = { version = "0.8.2", default-features = false }
 byteorder = { version = "1.3.4", default-features = false }
 rayon = { version = "1.3.0", optional = true }
 serde = { version = "1.0.106", features = ["derive"], default-features = false }
 bincode = { version = "1.3.3", default-features = false }
 subtle = { version = "2.4", features = ["i128"], default-features = false }
-zeroize = { version = "1.5", default-features = false }
 itertools = { version = "0.10.0", default-features = false }
 colored = { version = "2.0.0", default-features = false, optional = true }
 flate2 = { version = "1.0.14" }
@@ -66,7 +67,6 @@ std = [
     "byteorder/std",
     "serde/std",
     "subtle/std",
-    "zeroize/std",
     "itertools/use_std",
     "flate2/rust_backend",
 ]

README.md

@@ -187,7 +187,7 @@ fn produce_tiny_r1cs() -> (
   // To construct these matrices, we will use `curve25519-dalek` but one can use any other method.
 
   // a variable that holds a byte representation of 1
-  let one = Scalar::one().to_bytes();
+  let one = Scalar::ONE.to_bytes();
 
   // R1CS is a set of three sparse matrices A B C, where is a row for every
   // constraint and a column for every entry in z = (vars, 1, inputs)
@@ -224,10 +224,10 @@ fn produce_tiny_r1cs() -> (
   let z1 = Scalar::random(&mut csprng);
   let z2 = (z0 + z1) * i0; // constraint 0
   let z3 = (z0 + i1) * z2; // constraint 1
-  let z4 = Scalar::zero(); //constraint 2
+  let z4 = Scalar::ZERO; //constraint 2
 
   // create a VarsAssignment
-  let mut vars = vec![Scalar::zero().to_bytes(); num_vars];
+  let mut vars = vec![Scalar::ZERO.to_bytes(); num_vars];
   vars[0] = z0.to_bytes();
   vars[1] = z1.to_bytes();
   vars[2] = z2.to_bytes();
@@ -236,7 +236,7 @@ fn produce_tiny_r1cs() -> (
   let assignment_vars = VarsAssignment::new(&vars).unwrap();
 
   // create an InputsAssignment
-  let mut inputs = vec![Scalar::zero().to_bytes(); num_inputs];
+  let mut inputs = vec![Scalar::ZERO.to_bytes(); num_inputs];
   inputs[0] = i0.to_bytes();
   inputs[1] = i1.to_bytes();
   let assignment_inputs = InputsAssignment::new(&inputs).unwrap();

examples/cubic.rs

@@ -36,7 +36,7 @@ fn produce_r1cs() -> (
   let mut B: Vec<(usize, usize, [u8; 32])> = Vec::new();
   let mut C: Vec<(usize, usize, [u8; 32])> = Vec::new();
 
-  let one = Scalar::one().to_bytes();
+  let one = Scalar::ONE.to_bytes();
 
   // R1CS is a set of three sparse matrices A B C, where is a row for every
   // constraint and a column for every entry in z = (vars, 1, inputs)
@@ -80,15 +80,15 @@ fn produce_r1cs() -> (
   let i0 = z3 + Scalar::from(5u32); // constraint 3
 
   // create a VarsAssignment
-  let mut vars = vec![Scalar::zero().to_bytes(); num_vars];
+  let mut vars = vec![Scalar::ZERO.to_bytes(); num_vars];
   vars[0] = z0.to_bytes();
   vars[1] = z1.to_bytes();
   vars[2] = z2.to_bytes();
   vars[3] = z3.to_bytes();
   let assignment_vars = VarsAssignment::new(&vars).unwrap();
 
   // create an InputsAssignment
-  let mut inputs = vec![Scalar::zero().to_bytes(); num_inputs];
+  let mut inputs = vec![Scalar::ZERO.to_bytes(); num_inputs];
   inputs[0] = i0.to_bytes();
   let assignment_inputs = InputsAssignment::new(&inputs).unwrap();
 

profiler/nizk.rs

@@ -17,7 +17,7 @@ fn print(msg: &str) {
 
 pub fn main() {
   // the list of number of variables (and constraints) in an R1CS instance
-  let inst_sizes = vec![10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20];
+  let inst_sizes = [10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20];
 
   println!("Profiler:: NIZK");
   for &s in inst_sizes.iter() {

profiler/snark.rs

@@ -16,7 +16,7 @@ fn print(msg: &str) {
 
 pub fn main() {
   // the list of number of variables (and constraints) in an R1CS instance
-  let inst_sizes = vec![10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20];
+  let inst_sizes = [10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20];
 
   println!("Profiler:: SNARK");
   for &s in inst_sizes.iter() {

src/product_tree.rs

@@ -257,8 +257,8 @@ impl ProductCircuitEvalProof {
 
 impl ProductCircuitEvalProofBatched {
   pub fn prove(
-    prod_circuit_vec: &mut Vec<&mut ProductCircuit>,
-    dotp_circuit_vec: &mut Vec<&mut DotProductCircuit>,
+    prod_circuit_vec: &mut [&mut ProductCircuit],
+    dotp_circuit_vec: &mut [&mut DotProductCircuit],
     transcript: &mut Transcript,
   ) -> (Self, Vec<Scalar>) {
     assert!(!prod_circuit_vec.is_empty());

src/scalar/ristretto255.rs

@@ -13,7 +13,6 @@ use core::ops::{Add, AddAssign, Mul, MulAssign, Neg, Sub, SubAssign};
 use rand::{CryptoRng, RngCore};
 use serde::{Deserialize, Serialize};
 use subtle::{Choice, ConditionallySelectable, ConstantTimeEq, CtOption};
-use zeroize::Zeroize;
 
 // use crate::util::{adc, mac, sbb};
 /// Compute a + b + carry, returning the result and the new carry over.
@@ -359,12 +358,6 @@ where
   }
 }
 
-impl Zeroize for Scalar {
-  fn zeroize(&mut self) {
-    self.0 = [0u64; 4];
-  }
-}
-
 impl Scalar {
   /// Returns zero, the additive identity.
   #[inline]
@@ -609,22 +602,17 @@ impl Scalar {
     // externally, but there's no corresponding distinction for
     // field elements.
 
-    use zeroize::Zeroizing;
-
     let n = inputs.len();
     let one = Scalar::one();
 
-    // Place scratch storage in a Zeroizing wrapper to wipe it when
-    // we pass out of scope.
-    let scratch_vec = vec![one; n];
-    let mut scratch = Zeroizing::new(scratch_vec);
+    let mut scratch_vec = vec![one; n];
 
     // Keep an accumulator of all of the previous products
     let mut acc = Scalar::one();
 
     // Pass through the input vector, recording the previous
     // products in the scratch space
-    for (input, scratch) in inputs.iter().zip(scratch.iter_mut()) {
+    for (input, scratch) in inputs.iter().zip(scratch_vec.iter_mut()) {
       *scratch = acc;
 
       acc = acc * input;
@@ -641,7 +629,7 @@ impl Scalar {
 
     // Pass through the vector backwards to compute the inverses
     // in place
-    for (input, scratch) in inputs.iter_mut().rev().zip(scratch.iter().rev()) {
+    for (input, scratch) in inputs.iter_mut().rev().zip(scratch_vec.iter().rev()) {
       let tmp = &acc * input.clone();
       *input = &acc * scratch;
       acc = tmp;

src/sparse_mlpoly.rs

@@ -1154,7 +1154,7 @@ impl ProductLayerProof {
     };
 
     let (proof_ops, rand_ops) = ProductCircuitEvalProofBatched::prove(
-      &mut vec![
+      &mut [
         &mut row_read_A[0],
         &mut row_read_B[0],
         &mut row_read_C[0],
@@ -1168,7 +1168,7 @@ impl ProductLayerProof {
         &mut col_write_B[0],
         &mut col_write_C[0],
       ],
-      &mut vec![
+      &mut [
         &mut dotp_left_A[0],
         &mut dotp_right_A[0],
         &mut dotp_left_B[0],
@@ -1181,7 +1181,7 @@ impl ProductLayerProof {
 
     // produce a batched proof of memory-related product circuits
     let (proof_mem, rand_mem) = ProductCircuitEvalProofBatched::prove(
-      &mut vec![
+      &mut [
         &mut row_prod_layer.init,
         &mut row_prod_layer.audit,
         &mut col_prod_layer.init,