fn multiscalar_mul()

in src/backend/serial/scalar_mul/straus.rs [102:142]

• 31 lines of code
• 3 McCabe index (conditional complexity)

    fn multiscalar_mul<I, J>(scalars: I, points: J) -> EdwardsPoint
    where
        I: IntoIterator,
        I::Item: Borrow<Scalar>,
        J: IntoIterator,
        J::Item: Borrow<EdwardsPoint>,
    {
        use zeroize::Zeroizing;

        use backend::serial::curve_models::ProjectiveNielsPoint;
        use window::LookupTable;
        use traits::Identity;

        let lookup_tables: Vec<_> = points
            .into_iter()
            .map(|point| LookupTable::<ProjectiveNielsPoint>::from(point.borrow()))
            .collect();

        // This puts the scalar digits into a heap-allocated Vec.
        // To ensure that these are erased, pass ownership of the Vec into a
        // Zeroizing wrapper.
        let scalar_digits_vec: Vec<_> = scalars
            .into_iter()
            .map(|s| s.borrow().to_radix_16())
            .collect();
        let scalar_digits = Zeroizing::new(scalar_digits_vec);

        let mut Q = EdwardsPoint::identity();
        for j in (0..64).rev() {
            Q = Q.mul_by_pow_2(4);
            let it = scalar_digits.iter().zip(lookup_tables.iter());
            for (s_i, lookup_table_i) in it {
                // R_i = s_{i,j} * P_i
                let R_i = lookup_table_i.select(s_i[j]);
                // Q = Q + R_i
                Q = (&Q + &R_i).to_extended();
            }
        }

        Q
    }