Table of Contents
In this tutorial, you will learn about the shell sort algorithm and its implementation in Python, Java, C, and C++.
Shell sort is a generalized version of the insertion sort algorithm. It first sorts elements that are far apart from each other and successively reduces the interval between the elements to be sorted.
The interval between the elements is reduced based on the sequence used. Some of the optimal sequences that can be used in the shell sort algorithm are:
- Shell’s original sequence:
N/2 , N/4 , …, 1
- Knuth’s increments:
1, 4, 13, …, (3k
– 1) / 2
- Sedgewick’s increments:
1, 8, 23, 77, 281, 1073, 4193, 16577...4j+1+ 3·2j+ 1
- Hibbard’s increments:
1, 3, 7, 15, 31, 63, 127, 255, 511…
- Papernov & Stasevich increment:
1, 3, 5, 9, 17, 33, 65,...
- Pratt:
1, 2, 3, 4, 6, 9, 8, 12, 18, 27, 16, 24, 36, 54, 81....
Note: The performance of the shell sort depends on the type of sequence used for a given input array.
1. Working of Shell Sort
Suppose, we need to sort the following array.
Initial array
We are using the shell’s original sequence (N/2, N/4, ...1
) as intervals in our algorithm.
In the first loop, if the array size is N = 8
then, the elements lying at the interval of N/2 = 4
are compared and swapped if they are not in order.
The 0th element is compared with the 4th element.
If the 0th element is greater than the 4th one then, the 4th element is first stored in temp
variable and the 0th
element (ie. greater element) is stored in the 4th
position and the element stored in temp
is stored in the 0th
position.
Rearrange the elements at n/2 interval
This process goes on for all the remaining elements.
Rearrange all the elements at n/2 interval
In the second loop, an interval of N/4 = 8/4 = 2
is taken and again the elements lying at these intervals are sorted.
Rearrange the elements at n/4 interval
You might get confused at this point.
All the elements in the array lying at the current interval are compared.
The elements at 4th and 2nd
position are compared. The elements at 2nd and 0th
position are also compared. All the elements in the array lying at the current interval are compared.
The same process goes on for remaining elements.
Rearrange all the elements at n/4 interval
Finally, when the interval is N/8 = 8/8 =1
then the array elements lying at the interval of 1 are sorted. The array is now completely sorted.
Rearrange the elements at n/8 interval
2. Shell Sort Algorithm
shellSort(array, size) for interval i <- size/2n down to 1 for each interval "i" in array sort all the elements at interval "i" end shellSort
3. Shell Sort Code in Python, Java, and C/C++
Source code by Python Language:
# Shell sort in python def shellSort(array, n): # Rearrange elements at each n/2, n/4, n/8, ... intervals interval = n // 2 while interval > 0: for i in range(interval, n): temp = array[i] j = i while j >= interval and array[j - interval] > temp: array[j] = array[j - interval] j -= interval array[j] = temp interval //= 2 data = [9, 8, 3, 7, 5, 6, 4, 1] size = len(data) shellSort(data, size) print('Sorted Array in Ascending Order:') print(data)
Source code by Java Language:
// Shell sort in Java programming import java.util.Arrays; // Shell sort class ShellSort { // Rearrange elements at each n/2, n/4, n/8, ... intervals void shellSort(int array[], int n) { for (int interval = n / 2; interval > 0; interval /= 2) { for (int i = interval; i < n; i += 1) { int temp = array[i]; int j; for (j = i; j >= interval && array[j - interval] > temp; j -= interval) { array[j] = array[j - interval]; } array[j] = temp; } } } // Driver code public static void main(String args[]) { int[] data = { 9, 8, 3, 7, 5, 6, 4, 1 }; int size = data.length; ShellSort ss = new ShellSort(); ss.shellSort(data, size); System.out.println("Sorted Array in Ascending Order: "); System.out.println(Arrays.toString(data)); } }
Source code by C Language:
// Shell Sort in C programming #include <stdio.h> // Shell sort void shellSort(int array[], int n) { // Rearrange elements at each n/2, n/4, n/8, ... intervals for (int interval = n / 2; interval > 0; interval /= 2) { for (int i = interval; i < n; i += 1) { int temp = array[i]; int j; for (j = i; j >= interval && array[j - interval] > temp; j -= interval) { array[j] = array[j - interval]; } array[j] = temp; } } } // Print an array void printArray(int array[], int size) { for (int i = 0; i < size; ++i) { printf("%d ", array[i]); } printf("\n"); } // Driver code int main() { int data[] = {9, 8, 3, 7, 5, 6, 4, 1}; int size = sizeof(data) / sizeof(data[0]); shellSort(data, size); printf("Sorted array: \n"); printArray(data, size); }
Source code by C++ Language:
// Shell Sort in C++ programming #include <iostream> using namespace std; // Shell sort void shellSort(int array[], int n) { // Rearrange elements at each n/2, n/4, n/8, ... intervals for (int interval = n / 2; interval > 0; interval /= 2) { for (int i = interval; i < n; i += 1) { int temp = array[i]; int j; for (j = i; j >= interval && array[j - interval] > temp; j -= interval) { array[j] = array[j - interval]; } array[j] = temp; } } } // Print an array void printArray(int array[], int size) { int i; for (i = 0; i < size; i++) cout << array[i] << " "; cout << endl; } // Driver code int main() { int data[] = {9, 8, 3, 7, 5, 6, 4, 1}; int size = sizeof(data) / sizeof(data[0]); shellSort(data, size); cout << "Sorted array: \n"; printArray(data, size); }
4. Shell Sort Complexity
Time Complexity | |
---|---|
Best | O(nlog n) |
Worst | O(n2) |
Average | O(nlog n) |
Space Complexity | O(1) |
Stability | No |
Shell sort is an unstable sorting algorithm because this algorithm does not examine the elements lying in between the intervals.
4.1. Time Complexity
- Worst Case Complexity: less than or equal to
O(n2)
Worst case complexity for shell sort is always less than or equal toO(n2)
.
According to Poonen Theorem, worst case complexity for shell sort isΘ(Nlog N)2/(log log N)2)
orΘ(Nlog N)2/log log N)
orΘ(N(log N)2)
or something in between. - Best Case Complexity:
O(n*log n)
When the array is already sorted, the total number of comparisons for each interval (or increment) is equal to the size of the array. - Average Case Complexity:
O(n*log n)
It is aroundO(n1.25)
.
The complexity depends on the interval chosen. The above complexities differ for different increment sequences chosen. Best increment sequence is unknown.
4.2. Space Complexity:
The space complexity for shell sort is O(1)
.
5. Shell Sort Applications
Shell sort is used when:
- calling a stack is overhead.
uClibc
library uses this sort. - recursion exceeds a limit.
bzip2
compressor uses it. - Insertion sort does not perform well when the close elements are far apart. Shell sort helps in reducing the distance between the close elements. Thus, there will be less number of swappings to be performed.
6. Other Sorting Algorithms
- Bubble Sort
- Quicksort
- Insertion Sort
- Selection Sort