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sparse_hes_fun: Example and test
`

    # include <cppad/speed/sparse_hes_fun.hpp>
    # include <cppad/speed/uniform_01.hpp>
    # include <cppad/cppad.hpp>

    bool sparse_hes_fun(void)
    {     using CppAD::NearEqual;
         bool ok = true;

         typedef CppAD::AD<double> ADScalar;

         size_t j, k;
         double eps = 10. * CppAD::numeric_limits<double>::epsilon();
         size_t n   = 5;
         size_t m   = 1;
         size_t K   = 2 * n;
         CppAD::vector<size_t>       row(K),  col(K);
         CppAD::vector<double>       x(n),    ypp(K);
         CppAD::vector<ADScalar>     a_x(n),  a_y(m);

         // choose x
         for(j = 0; j < n; j++)
              a_x[j] = x[j] = double(j + 1);

         // choose row, col
         for(k = 0; k < K; k++)
         {     row[k] = k % 3;
              col[k] = k / 3;
         }
         for(k = 0; k < K; k++)
         {     for(size_t k1 = 0; k1 < K; k1++)
                   assert( k == k1 || row[k] != row[k1] || col[k] != col[k1] );
         }

         // declare independent variables
         Independent(a_x);

         // evaluate function
         size_t order = 0;
         CppAD::sparse_hes_fun<ADScalar>(n, a_x, row, col, order, a_y);

         // evaluate Hessian
         order = 2;
         CppAD::sparse_hes_fun<double>(n, x, row, col, order, ypp);

         // use AD to evaluate Hessian
         CppAD::ADFun<double>   f(a_x, a_y);
         CppAD::vector<double>  hes(n * n);
         // compoute Hessian of f_0 (x)
         hes = f.Hessian(x, 0);

         for(k = 0; k < K; k++)
         {     size_t index = row[k] * n + col[k];
              ok &= NearEqual(hes[index], ypp[k] , eps, eps);
         }
         return ok;
    }

`

Input File: speed/example/sparse_hes_fun.cpp