Selection Sort Algorithms

Selection sort is an algorithm that selects the smallest element from an unsorted list in each iteration and places that element at the beginning of the unsorted list.

How Selection Sort Works?
Set the first element as minimum.
Selection Sort Steps
Select first element as minimum
Compare minimum with the second element. If the second element is smaller than minimum, assign the second element as minimum.

Compare minimum with the third element. Again, if the third element is smaller, then assign minimum to the third element otherwise do nothing. The process goes on until the last element.
Selection Sort Steps
Compare minimum with the remaining elements
After each iteration, minimum is placed in the front of the unsorted list.
Selection Sort Steps
Swap the first with minimum
For each iteration, indexing starts from the first unsorted element. Step 1 to 3 are repeated until all the elements are placed at their correct positions.
Selection Sort Steps
The first iteration

Selection sort steps
The second iteration

Selection sort steps
The third iteration

Selection sort steps
The fourth iteration
Selection Sort Algorithm
selectionSort(array, size)
repeat (size - 1) times
set the first unsorted element as the minimum
for each of the unsorted elements
if element < currentMinimum
set element as new minimum
swap minimum with first unsorted position
end selectionSort
Python, Java and C/C++ Examples
Python
Java
C
C++

Selection sort in Python

def selectionSort(array, size):

for step in range(size):
    min_idx = step

    for i in range(step + 1, size):

        # to sort in descending order, change > to < in this line
        # select the minimum element in each loop
        if array[i] < array[min_idx]:
            min_idx = i

    # put min at the correct position
    (array[step], array[min_idx]) = (array[min_idx], array[step])

data = [-2, 45, 0, 11, -9]
size = len(data)
selectionSort(data, size)
print('Sorted Array in Ascending Order:')
print(data)
Complexity
Cycle Number of Comparison
1st (n-1)
2nd (n-2)
3rd (n-3)
... ...
last 1
Number of comparisons: (n - 1) + (n - 2) + (n - 3) + ..... + 1 = n(n - 1) / 2 nearly equals to n2.

Complexity = O(n2)

Also, we can analyze the complexity by simply observing the number of loops. There are 2 loops so the complexity is n*n = n2.

Time Complexities:

Worst Case Complexity: O(n2)
If we want to sort in ascending order and the array is in descending order then, the worst case occurs.
Best Case Complexity: O(n2)
It occurs when the array is already sorted
Average Case Complexity: O(n2)
It occurs when the elements of the array are in jumbled order (neither ascending nor descending).
The time complexity of the selection sort is the same in all cases. At every step, you have to find the minimum element and put it in the right place. The minimum element is not known until the end of the array is not reached.

Space Complexity:

Space complexity is O(1) because an extra variable temp is used.

Selection Sort Applications
The selection sort is used when:

a small list is to be sorted
cost of swapping does not matter
checking of all the elements is compulsory
cost of writing to a memory matters like in flash memory (number of writes/swaps is O(n) as compared to O(n2) of bubble sort)