$\mathrm{with}\left(\mathrm{CodeGeneration}\right)\:$

$\mathrm{Julia}\left(\sqrt{a^2\+b^2\+c^2}\right)$

cg = sqrt(a ^ 2 + b ^ 2 + c ^ 2)

$\mathrm{Julia}\left(m\to \mathrm{add}\left(i\,i\=1..m\right)\right)$

function cg0(m)

    r = 0
    for i = 1:m
        r = r + i
    return(r)
end

$\mathrm{Julia}\left(\left[\begin{array}{rr}1& 2\\ 3& 4\end{array}\right]\right)$

cg1 = [1 2; 3 4]

$\mathrm{Julia}\&lpar;\&lcub;\begin{array}{cc}-v^3\&plus;3v\&plus;1& v<1\\ 2v^3-9v^2\&plus;12v-2& v<2\\ -v^3\&plus;9v^2-24v\&plus;22& \mathrm{otherwise}\end{array}\&rpar;$

cg2 = -v ^ 3 + 3 * v + 1 ? v < 1 : 2 * v ^ 3 - 9 * v ^ 2 + 12 * v - 2 ? v < 2 : -v ^ 3 + 9 * v ^ 2 - 24 * v + 22

$\mathrm{Julia}\left(\left(M\&comma;n\right)\to M - x \mathrm{LinearAlgebra}:-\mathrm{IdentityMatrix}\left(n\right)\right)$

cg3(M,n) = M - x * eye(n)

$\mathrm{Julia}\left(\mathrm{\_C1}\mathrm{BesselJ}\left(\mathrm{\nu }\&comma;x\right)\&plus;\mathrm{\_C2}\mathrm{BesselY}\left(\mathrm{\nu }\&comma;x\right)\right)$

cg4 = _C1 * besselj(nu, x) + _C2 * bessely(nu, x)

$\mathrm{Julia}\left(\&apos;\mathrm{Statistics}:-\mathrm{Mean}\left(\left[5\&comma;2\&comma;1\&comma;4\&comma;3\right]\right)\&apos;\right)$

cg5 = mean([5,2,1,4,3])

$\mathrm{Julia}\left(\&apos;\mathrm{Statistics}:-\mathrm{Median}\left(\left[5\&comma;2\&comma;1\&comma;4\&comma;3\right]\right)\&apos;\right)$

cg6 = median([5,2,1,4,3])

$\mathrm{Julia}\left(\&apos;\mathrm{Statistics}:-\mathrm{StandardDeviation}\left(\left[5\&comma;2\&comma;1\&comma;4\&comma;3\right]\right)\&apos;\right)$

cg7 = std([5,2,1,4,3])

$\mathrm{Julia}\left(\mathrm{Statistics}:-\mathrm{PDF}\left(\mathrm{LogNormal}\left(0\&comma;1\right)\&comma;x\right)\right)$

cg9 = 0 ? x < 0 : 1 / x * sqrt(2) * pi ^ (-1//2) * exp(-log(x) ^ 2 / 2) / 2