srand() sets the seed which is used by rand to generate “random” numbers. If you don’t call srand before your first call to rand, it’s as if you had called srand(1) to set the seed to one.
In short, srand() — Set Seed for rand() Function.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.

In this article we will discuss how to implement QuickSort using random pivoting. In QuickSort we first partition the array in place such that all elements to the left of the pivot element are smaller, while all elements to the right of the pivot are greater that the pivot. Then we recursively call the same procedure for left and right subarrays.
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Unlike merge sort we don’t need to merge the two sorted arrays. Thus Quicksort requires lesser auxillary space than Merge Sort, which is why it is often preferred to Merge Sort.Using a randomly generated pivot we can further improve the time complexity of QuickSort.
We have discussed at two popular methods for partioning the arrays-Hoare’s vs Lomuto partition scheme
It is advised that the reader has read that article or knows how to implement the QuickSort using either of the two partition schemes.
Algorithm for random pivoting using Lomuto Partitioning
Algorithm for random pivoting using Hoare Partitioning

Below is the CPP implementation of the Algorithms

Lomuto (C++)

C++ Get Random Number

/* C++ implementation QuickSort using Lomuto's partition
#include <cstdlib>
usingnamespacestd;
/* This function takes last element as pivot, places
the pivot element at its correct position in sorted
array, and places all smaller (smaller than pivot)
to left of pivot and all greater elements to right
intpartition(intarr[], intlow, inthigh)
intpivot = arr[high]; // pivot
inti = (low - 1); // Index of smaller element
for(intj = low; j <= high - 1; j++) {
// If current element is smaller than or
if(arr[j] <= pivot) {
i++; // increment index of smaller element
}
swap(arr[i + 1], arr[high]);
}
// Generates Random Pivot, swaps pivot with
intpartition_r(intarr[], intlow, inthigh)
// Generate a random number in between
srand(time(NULL));
swap(arr[random], arr[high]);
returnpartition(arr, low, high);
arr[] --> Array to be sorted,
high --> Ending index */
{
/* pi is partitioning index, arr[p] is now
intpi = partition_r(arr, low, high);
// Separately sort elements before
quickSort(arr, low, pi - 1);
}
voidprintArray(intarr[], intsize)
inti;
printf('%d ', arr[i]);
}
// Driver program to test above functions
{
intn = sizeof(arr) / sizeof(arr[0]);
printf('Sorted array:');
return0;

Hoare (C++)

partition scheme. */
#include <iostream>
/* This function takes last element as pivot, places
the pivot element at its correct position in sorted
array, and places all smaller (smaller than pivot)
to left of pivot and all greater elements to right
intpartition(intarr[], intlow, inthigh)
intpivot = arr[low];
// or equal to pivot
i++;
// or equal to pivot
j--;
if(i >= j)
}
// end element and calls the partition function
// In Hoare partition the low element is selected
intpartition_r(intarr[], intlow, inthigh)
// Generate a random number in between
srand(time(NULL));
swap(arr[random], arr[low]);
returnpartition(arr, low, high);
arr[] --> Array to be sorted,
high --> Ending index */
{
/* pi is partitioning index, arr[p] is now
intpi = partition_r(arr, low, high);
// Separately sort elements before
quickSort(arr, low, pi);
}
voidprintArray(intarr[], intn)
for(inti = 0; i < n; i++)
printf(');
intmain()
intarr[] = { 10, 7, 8, 9, 1, 5 };
quickSort(arr, 0, n - 1);
printArray(arr, n);
}

Output:
Notes
  • Using random pivoting we improve the expected or average time complexity to O (N log N). The Worst Case complexity is still O ( N^2 ).