fix: typos in curve.rs

src/bn256/engine.rs

@@ -271,7 +271,7 @@ impl G2Prepared {
 
             r.y -= &tmp2;
 
-            // up to here everything was by algorith, line 11
+            // up to here everything was by algorithm, line 11
             // use R instead of new T
 
             // tmp3 is the first part of line 12

src/derive/curve.rs

@@ -523,7 +523,7 @@ macro_rules! new_curve_impl {
             }
 
             fn jacobian_coordinates(&self) -> ($base, $base, $base) {
-                // Homogenous to Jacobian
+                // Homogeneous to Jacobian
                 let x = self.x * self.z;
                 let y = self.y * self.z.square();
                 (x, y, self.z)
@@ -563,7 +563,7 @@ macro_rules! new_curve_impl {
             }
 
             fn new_jacobian(x: Self::Base, y: Self::Base, z: Self::Base) -> CtOption<Self> {
-                // Jacobian to homogenous
+                // Jacobian to homogeneous
                 let z_inv = z.invert().unwrap_or($base::zero());
                 let p_x = x * z_inv;
                 let p_y = y * z_inv.square();

src/derive/field.rs

@@ -66,7 +66,7 @@ macro_rules! field_common {
             #[cfg(feature = "asm")]
             const fn montgomery_form(val: [u64; 4], r: $field) -> $field {
                 // Converts a 4 64-bit limb value into its congruent field representation.
-                // If `val` representes a 256 bit value then `r` should be R^2,
+                // If `val` represents a 256 bit value then `r` should be R^2,
                 // if `val` represents the 256 MSB of a 512 bit value, then `r` should be R^3.
 
                 let (r0, carry) = mac(0, val[0], r.0[0], 0);

src/ff_ext/jacobi.rs

@@ -355,7 +355,7 @@ pub fn jacobi<const L: usize>(n: &[u64], d: &[u64]) -> i64 {
         // When each "approximation" variable has the same value as the corresponding "precise"
         // one, the computation is accomplished using the short-arithmetic method of the Jacobi
         // symbol calculation by means of the binary Euclidean algorithm. This approach aims at
-        // avoiding the parts of the final computations, which are related to long arithmetics
+        // avoiding the parts of the final computations, which are related to long arithmetic
         if precise {
             return jacobinary(a, b, t);
         }

src/msm.rs

@@ -221,7 +221,7 @@ mod test {
         }
     }
 
-    // keeping older implementation it here for baseline comparision, debugging & benchmarking
+    // keeping older implementation it here for baseline comparison, debugging & benchmarking
     fn multiexp_serial<C: CurveAffine>(coeffs: &[C::Scalar], bases: &[C], acc: &mut C::Curve) {
         let coeffs: Vec<_> = coeffs.iter().map(|a| a.to_repr()).collect();
 

src/pluto_eris/engine.rs

@@ -285,7 +285,7 @@ impl G2Prepared {
 
             r.y -= &tmp2;
 
-            // up to here everything was by algorith, line 11
+            // up to here everything was by algorithm, line 11
             // use R instead of new T
 
             // tmp3 is the first part of line 12