# Where is pivoting done in the Crout decomposition algorithm?

Consider the following code, found on wikipedia, that implements the Crout decomposition algorithm:

    void crout(double const **A, double **L, double **U, int n) {
int i, j, k;
double sum = 0;

for (i = 0; i < n; i++) {
U[i][i] = 1;
}

for (j = 0; j < n; j++) {
for (i = j; i < n; i++) {
sum = 0;
for (k = 0; k < j; k++) {
sum = sum + L[i][k] * U[k][j];
}
L[i][j] = A[i][j] - sum;
}

for (i = j; i < n; i++) {
sum = 0;
for(k = 0; k < j; k++) {
sum = sum + L[j][k] * U[k][i];
}
if (L[j][j] == 0) {
printf("det(L) close to 0!\n Can't divide by 0...\n");
exit(EXIT_FAILURE);
}
U[j][i] = (A[j][i] - sum) / L[j][j];
}
}
}


Which part is responsible for pivoting?

The thing is, I've read that partial pivoting is still a rather non-trivial operation (on the order $O(n^2)$), but the above algorithm seems similar in terms of complexity to the "naive" LU decomposition without any pivoting.

To check, I've run the algorithm on my 28x28 test matrix

[ 0 0.291601633 0 -0.062262937 0 0 0 0 0 -0.22949092 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0.291601633 0 -0.062262937 0 0 0 0 0 -0.22949092 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 -0.062262937 0 0.633860174 0 -0.203470344 0 -0.185648901 0 -0.182968732 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ -0.062262937 0 0.633860174 0 -0.203470344 0 -0.185648901 0 -0.182968732 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 -0.203470344 0 0.386208493 0 -0.18368887 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 -0.203470344 0 0.386208493 0 -0.18368887 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 -0.185648901 0 -0.18368887 0 1.163032501 0 -0.044175498 0 0 0 -0.20912 0 0 0 -0.55618 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 -0.185648901 0 -0.18368887 0 1.163032501 0 -0.044175498 0 0 0 -0.20912 0 0 0 -0.55618 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 -0.22949092 0 -0.182968732 0 0 0 -0.044175498 0 0.702145321 0 -0.25202 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ -0.22949092 0 -0.182968732 0 0 0 -0.044175498 0 0.702145321 0 -0.25202 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 -0.25202 0 0.883882188 0 0 0 0 0 0 0 0 0 -0.220414179 0 -0.28380561 0 -0.14610303 0 0 ]
[ 0 0 0 0 0 0 0 0 -0.25202 0 0.883882188 0 0 0 0 0 0 0 0 0 -0.220414179 0 -0.28380561 0 -0.14610303 0 0 0 ]
[ 0 0 0 0 0 0 0 -0.20912 0 0 0 0 0 0.49528 0 -0.17615 0 -0.11001 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 -0.20912 0 0 0 0 0 0.49528 0 -0.17615 0 -0.11001 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.17615 0 0.17615 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 0 -0.17615 0 0.17615 0 0 0 0 0 0 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 -0.55618 0 0 0 0 0 -0.11001 0 0 0 1.033363204 0 -0.090289125 0 0 0 0 0 0 0 -0.298767964 ]
[ 0 0 0 0 0 0 -0.55618 0 0 0 0 0 -0.11001 0 0 0 1.033363204 0 -0.090289125 0 0 0 0 0 0 0 -0.298767964 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.090289125 0 0.299090395 0 -0.208861407 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.090289125 0 0.299090395 0 -0.208861407 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 -0.220414179 0 0 0 0 0 0 0 -0.208861407 0 0.429181968 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 -0.220414179 0 0 0 0 0 0 0 -0.208861407 0 0.429181968 0 0 0 0 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 -0.28380561 0 0 0 0 0 0 0 0 0 0 0 0.570852385 0 -0.29792224 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 -0.28380561 0 0 0 0 0 0 0 0 0 0 0 0.570852385 0 -0.29792224 0 0 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 -0.14610303 0 0 0 0 0 0 0 0 0 0 0 -0.29792224 0 0.818338896 0 -0.387730558 ]
[ 0 0 0 0 0 0 0 0 0 0 -0.14610303 0 0 0 0 0 0 0 0 0 0 0 -0.29792224 0 0.818338896 0 -0.387730558 0 ]
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.298767964 0 0 0 0 0 0 0 -0.387730558 0 0.68647389 ]
[ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -0.298767964 0 0 0 0 0 0 0 -0.387730558 0 0.68647389 0 ]


which is invertible (you can check here), when it returned a number NaNs and Infinities.

That algorithm doesn't do any pivoting. It requires non-zero elements on the diagonal of A to work, otherwise you divide by zero. Note the check:
if (L[j][j] == 0) {