Example of O(n!)?

Question

What is an example (in code) of a O(n!) function? It should take appropriate number of operations to run in reference to n; that is, I\'m asking a

Answer 1

I think I'm a bit late, but I find snailsort to be the best example of O(n!) deterministic algorithm. It basically finds the next permutation of an array until it sorts it.

It looks like this:

template <class Iter> 
void snail_sort(Iter first, Iter last)
{
    while (next_permutation(first, last)) {}
}

Answer 2

In C#

Wouldn't this be O(N!) in space complexity? because, string in C# is immutable.

string reverseString(string orgString) {
    string reversedString = String.Empty;

    for (int i = 0; i < orgString.Length; i++) {
        reversedString += orgString[i];
    }

    return reversedString;
}

Answer 3

Add to up k function

This is a simple example of a function with complexity O(n!) given an array of int in parameter and an integer k. it returns true if there are two items from the array x+y = k , For example : if tab was [1, 2, 3, 4] and k=6 the returned value would be true because 2+4=6

public boolean addToUpK(int[] tab, int k) {

        boolean response = false;

        for(int i=0; i<tab.length; i++) {

            for(int j=i+1; j<tab.length; j++) {

                if(tab[i]+tab[j]==k) {
                    return true;
                }

            }

        }
        return response;
    }

As a bonus this is a unit test with jUnit, it works fine

@Test
    public void testAddToUpK() {

        DailyCodingProblem daProblem = new DailyCodingProblemImpl();

        int tab[] = {10, 15, 3, 7};
        int k = 17;
        boolean result = true; //expected result because 10+7=17
        assertTrue("expected value is true", daProblem.addToUpK(tab, k) == result);

        k = 50;
        result = false; //expected value because there's any two numbers from the list add up to 50
        assertTrue("expected value is false", daProblem.addToUpK(tab, k) == result);
    }

Answer 4

You are right the recursive calls should take exactly n! time. here is a code like to test factorial time for n different values. Inner loop runs for n! time for different values of j, so the complexity of inner loop is Big O(n!)

public static void NFactorialRuntime(int n)
    {
        Console.WriteLine(" N   Fn   N!");
        for (int i = 1; i <= n; i++)  // This loop is just to test n different values
        {
            int f = Fact(i);
            for (int j = 1; j <= f; j++)  // This is Factorial times
            {  ++x; }
            Console.WriteLine(" {0}   {1}   {2}", i, x, f);
            x = 0;
        }
    }

Here are the test result for n = 5, it iterate exactly factorial time.

  N   Fn   N!
  1   1   1
  2   2   2
  3   6   6
  4   24   24
  5   120   120

Exact function with time complexity n!

// Big O(n!)
public static void NFactorialRuntime(int n)
    {
        for (int j = 1; j <= Fact(i); j++) {  ++x; }
        Console.WriteLine(" {0}   {1}   {2}", i, x, f);
    }

Answer 5

@clocksmith You are absolutely correct. This is not calculating n!. Nor is it of O(n!). I ran it collected the data in the table below. Please compare column 2 and three. (#nF is the # of calls to nFacRuntimeFunc)

n #nF n!

0    0      1
1    1      1
2    4      2
3    15     6
4    65     24
5    325    120
6    1956   720
7    13699  5040

So clearly if performs much worse than O(n!). Below is the a sample code for calculating n! recursively. you will note that its of O(n) order.

int Factorial(int n)
{
   if (n == 1)
      return 1;
   else
      return n * Factorial(n-1);
}

Answer 6

The recursive method you probably learned for taking the determinant of a matrix (if you took linear algebra) takes O(n!) time. Though I dont particularly feel like coding that all up.