$$\begin{gathered} f:=\mathbf{proc}\left(x\,y\,z\right) \\ \mathbf{return} x\*y - y\*z\+x\*z \\ \mathbf{end} \mathbf{proc}\: \end{gathered}$$$C\left(f\right)$

double f (double x, double y, double z)
{
  return(x * y - y * z + x * z);
}

$C\left(f\,\mathrm{defaulttype}\=\mathrm{integer}\right)$

int f (int x, int y, int z)

{
  return(x * y - y * z + x * z);
}

$$\begin{gathered} f:=\mathbf{proc}\left(x::\mathrm{float}\,y\,z\right) \\ \mathbf{return} x\*y - y\*z\+x\*z \\ \mathbf{end} \mathbf{proc}\: \end{gathered}$$$C\left(f\,\mathrm{defaulttype}\=\mathrm{integer}\right)$

double f (double x, double y, double z)
{
  return(x * y - y * z + x * z);
}

$C\left(f\,\mathrm{defaulttype}\=\mathrm{integer}\,\mathrm{deducetypes}\=\mathrm{false}\right)$

double f (double x, int y, int z)

{
  return(x * (double) y - (double) (y * z) + x * (double) z);
}

$C\left(f\,\mathrm{defaulttype}\=\mathrm{integer}\,\mathrm{deducetypes}\=\mathrm{false}\,\mathrm{coercetypes}\=\mathrm{false}\right)$

double f (double x, int y, int z)

{
  return(x * y - y * z + x * z);
}

$C\left(1\+x\+y\,\mathrm{declare}\=\left[x::\mathrm{float}\,y::\mathrm{integer}\right]\right)$

cg3 = 0.1e1 + x + (double) y;

$\mathrm{cs}:=\left[s\=1.0\+x\,t\=\ln \left(x\right){\ⅇ}^{-x}\,r\={\ⅇ}^{-x}\+xt\right]\:$$\mathrm{Java}\left(\mathrm{cs}\,\mathrm{optimize}\right)$

s = 0.10e1 + x;
t1 = Math.log(x);
t2 = Math.exp(-x);
t = t1 * t2;
r = x * t + t2;

$s:=\mathrm{Java}\left(\log \left(x\right)\+\sin \left(y\right)\,\mathrm{output}\=\mathrm{string}\right)$

$s:=''cg4\; =\; Math.log(x)\; +\; Math.sin(y);''$

$s≔\mathrm{JavaScript}\left(\log \left(x\right)\+\sin \left(y\right)\,\mathrm{output}\=\mathrm{string}\right)$

$s:=''cg5\; =\; Math.log(x)\; +\; Math.sin(y);''$

$s≔\mathrm{CurveFitting}\left[\mathrm{Spline}\right]\left(\left[\left[0\,0\right]\,\left[1\,1\right]\,\left[2\,4\right]\,\left[3\,3\right]\,\left[4\,2\right]\right]\,v\right)$

$s:=\&lcub;\begin{array}{cc}\frac{23}{28}{v}^3\&plus;\frac{5}{28}v& v<1\\ -\frac{59}{28}{v}^3\&plus;\frac{123}{14}{v}^2-\frac{241}{28}v\&plus;\frac{41}{14}& v<2\\ \frac{45}{28}{v}^3-\frac{27}{2}{v}^2\&plus;\frac{1007}{28}v-\frac{375}{14}& v<3\\ -\frac{9}{28}{v}^3\&plus;\frac{27}{7}{v}^2-\frac{451}{28}v\&plus;\frac{177}{7}& \mathrm{otherwise}\end{array}$

$p≔\mathrm{unapply}\left(s\&comma;v\right)$

$p:=v\&rarr;\mathrm{piecewise}\left(v<1\&comma;\frac{23}{28}{v}^3\&plus;\frac{5}{28}v\&comma;v<2\&comma;-\frac{59}{28}{v}^3\&plus;\frac{123}{14}{v}^2-\frac{241}{28}v\&plus;\frac{41}{14}\&comma;v<3\&comma;\frac{45}{28}{v}^3-\frac{27}{2}{v}^2\&plus;\frac{1007}{28}v-\frac{375}{14}\&comma;-\frac{9}{28}{v}^3\&plus;\frac{27}{7}{v}^2-\frac{451}{28}v\&plus;\frac{177}{7}\right)$

$\mathrm{Fortran}\left(p\&comma;\mathrm{declare}\&equals;\left[v::\mathrm{float}\right]\right)$

Warning, procedure/module options ignored

      doubleprecision function p (v)
        doubleprecision v
        if (v .lt. 0.1D1) then
          p = 0.23D2 / 0.28D2 * v ** 3 + 0.5D1 / 0.28D2 * v
          return
        else if (v .lt. 0.2D1) then
          p = -0.59D2 / 0.28D2 * v ** 3 + 0.123D3 / 0.14D2 * v ** 2 - 0.
     #241D3 / 0.28D2 * v + 0.41D2 / 0.14D2
          return
        else if (v .lt. 0.3D1) then
          p = 0.45D2 / 0.28D2 * v ** 3 - 0.27D2 / 0.2D1 * v ** 2 + 0.100
     #7D4 / 0.28D2 * v - 0.375D3 / 0.14D2
          return
        else
          p = -0.9D1 / 0.28D2 * v ** 3 + 0.27D2 / 0.7D1 * v ** 2 - 0.451
     #D3 / 0.28D2 * v + 0.177D3 / 0.7D1
          return
        end if
      end

$$\begin{gathered} f:=\mathbf{proc}\left(x::\mathrm{float}\&comma;y::\mathrm{float}\right) \\ \mathbf{local} t\colon\colon \mathrm{float}\&semi; \\ t≔\exp \left(\&minus;x\right)\&semi; \\ \mathbf{return} y\&ast;t\&plus;t\&semi; \\ \mathbf{end} \mathbf{proc}\&colon; \end{gathered}$$

$g≔\mathrm{codegen}\left[\mathrm{GRADIENT}\right]\left(f\right)$

$g:=\mathbf{proc}\left(x::\mathrm{float}\&comma;y::\mathrm{float}\right)\mathbf{local}\mathrm{dfr0}\&comma;t::\mathrm{float}\&semi;t:=\exp \left(\&minus;x\right)\&semi;\mathrm{dfr0}:=\mathrm{array}\left(1..1\right)\&semi;\mathrm{dfr0}\&lsqb;1\&rsqb;:=y\&plus;1\&semi;\mathbf{return}\&minus;\mathrm{dfr0}\&lsqb;1\&rsqb;\&ast;\exp \left(\&minus;x\right)\&comma;t\mathbf{end\; proc}$

$C\left(g\&comma;\mathrm{optimize}\right)$

#include <math.h>

void g (double x, double y, double cgret[2])
{
  double dfr0[1];
  double t;
  t = exp(-x);
  dfr0[0] = 0;
  dfr0[0] = y + 0.1e1;
  cgret[0] = -dfr0[0] * t;
  cgret[1] = t;
}

$\mathrm{MatlabMatrix}≔\left[\begin{array}{rr}3& 1\\ 1& 3\end{array}\right]\&colon;$

$\mathrm{Matlab}\left(\mathrm{MatlabMatrix}\right)\&semi;$

cg6 = [3 1; 1 3;];

$\mathrm{Matlab}\&lpar;\&apos;\mathrm{LinearAlgebra}:-\mathrm{Eigenvalues}\&apos;\&lpar;\mathrm{MatlabMatrix}\&rpar;\&rpar;$

cg7 = eig([3 1; 1 3;]);

$\mathrm{RList}≔\left[4\&comma;8\&comma;15\&comma;16\&comma;23\&comma;42\right]\&colon;$

$R\left(\mathrm{RList}\right)\&semi;$

cg8 <- c(4,8,15,16,23,42)

$R\left(\&apos;\mathrm{Statistics}:-\mathrm{FivePointSummary}\&apos;\left(\mathrm{RList}\right)\right)$

cg9 <- fivenum(c(4,8,15,16,23,42))

$R\left(\&apos;\mathrm{Statistics}:-\mathrm{Mean}\&apos;\left(\mathrm{RList}\right)\right)$

cg10 <- mean(c(4,8,15,16,23,42))

$R\left(\mathrm{Statistics}:-\mathrm{Median}\left(\mathrm{RList}\right)\right)$

cg11 <- 0.155000000000000000e2

$R\left(\&apos;\mathrm{Statistics}:-\mathrm{Histogram}\&apos;\left(\mathrm{RList}\&comma; \mathrm{color}\&equals;''Orange''\right)\right)$

cg12 <- hist(c(4,8,15,16,23,42), col = "Orange")