shell sort using hibbard increment

I'm new to C. I want to do an experiment with shell sort using hibbard increment in C. And, in order to test the worst case, I always build a reversed array according to the input size. I expect to see the running time following the time complexity O(n^1.5). However, my output somehow follows the time complexity O(n). The following is my code. I would appreciate it if someone could help me find where the problem is.

#include <stdlib.h>
#include <stdio.h>
#include <time.h>
#include <math.h>

int get_input() {
  int input;
  printf("Please type input size(n): ");
  if(scanf("%d", &input) == 0) {
    fscanf(stdin, "%*[^\n]%*c");
  }
  return input;
}

int* build_data(int* array, int size) {
  array = malloc(sizeof(int) * size);
  for(int i=0; i < size; i++) {
    array[i] = size - i;
  }
  return array;
}

double record_time(int* array, int size, void (*fp)(int*, int)) {
  clock_t begin = clock();
  (*fp)(array, size);
  clock_t end = clock();

  return (double)(end - begin) / CLOCKS_PER_SEC;
}

void shell_sort(int* array, int size) {
  int* h_inc;
  int h_size;

  h_size = floor(log(size+1)/log(2));
  h_inc = malloc(sizeof(int) * h_size);
  for(int i=0; i < h_size; i++) {
    h_inc[i] = pow(2, i+1) - 1;
  }

  int i, j, tmp;

  for (int r = (h_size - 1); r >= 0; r--) {
    int gap = h_inc[r];

    for(i = gap; i < size; i++) {
      tmp = array[i];

      for(j = i; j >= gap && tmp < array[j-gap]; j-=gap) {
        array[j] = array[j-gap];
      }
      array[j] = tmp;
    }
  }

  free(h_inc);
  return;
}

int main() {
  while(1) {
    int size;
    int* data;
    double time_elapsed;

    size = get_input();
    if (size <= 0) { break; }

    data = build_data(data, size);
    time_elapsed = record_time(data, size, shell_sort);

    printf("Elapsed time: %f sec\n", time_elapsed);
    free(data);
  }
  return 0;
}

My output is:

Please type input size(n): 10000
Elapsed time: 0.001168 sec
Please type input size(n): 50000
Elapsed time: 0.006094 sec
Please type input size(n): 100000
Elapsed time: 0.010946 sec
Please type input size(n): 500000
Elapsed time: 0.054341 sec
Please type input size(n): 1000000
Elapsed time: 0.118640 sec
Please type input size(n): 5000000
Elapsed time: 0.618815 sec
Please type input size(n): 10000000
Elapsed time: 1.332671 sec

I guess we are comparing different things here. Time complexity and time taken to run a program is different. Time complexity can be simply said as asymptotic behavior of running time as input size tends to infinity.

Now you are saying that it is saying that it is following O(n). I guess you are looking that the two inputs and considering the multipicative increment in the time. It might be possible that your algorithm is running in An^1.5+bn+C cycles. So first of all you can't compare...exactly. You can say as input increases it would be asymtotically nearer to a function which is proprtionate to n^1.5.

Direct correlation between program run time and complexity is not what you should look for. Rather you can consider that from the basic oprations done in the program.

If you think that we can consider time complexity from running time entirely then I guess we need not have to consider those basic operations and all that.