![Example
arr[] = 19, 5, 7, 12
// Find the minimum element in arr[0...3]
// and place it at beginning
5, 19, 7, 12
// Find the minimum element in arr[1...3]
// and place it at beginning of arr[1...3]
5, 7, 19, 12
// Find the minimum element in arr[2...3]
// and place it at beginning of arr[2...3]
5, 7, 12, 19](https://image.slidesharecdn.com/selectionsort-171120131551/85/Selection-sort-4-320.jpg)
![C++ .
void selectionSort(int a[], int len)
{
int min, i, j ;
for(i=0; i<len-1; i++)
{
min = i ;
for(j=i+1; j<len; j++)
{
if(a[j] < a[min])
min = j ;
}
swap(&a[i], &a[min]) ;
}
}](https://image.slidesharecdn.com/selectionsort-171120131551/85/Selection-sort-7-320.jpg)
![JAVA .
void sort(int a[])
{
int len = a.length, min;
for (int i = 0; i < len-1; i++)
{
min = i;
for (int j=i+1; j<len; j++)
if (a[j] < a[min])
min = j;
int temp = a[min];
a[min] = a[i];
a[i] = temp;
}
}](https://image.slidesharecdn.com/selectionsort-171120131551/85/Selection-sort-8-320.jpg)
![Python .
def selectionSort(a):
for i in range(len(a)):
min = i
for j in range(i+1, len(a)):
if a[min] > a[j]:
min = j
a[i], a[min] = a[min], a[i]](https://image.slidesharecdn.com/selectionsort-171120131551/85/Selection-sort-9-320.jpg)
![Execution .
Input array : [4, 6, 3, 2, 1, 9, 7]
Swap => 4, 1
First Action : [1, 6, 3, 2, 4, 9, 7]
Swap => 6, 2
Second Action : [1, 2, 3, 6, 4, 9, 7]
Swap => 6, 4
Fourth Action : [1, 2, 3, 4, 6, 9, 7]
Swap => 9, 7
Sixth Action : [1, 2, 3, 4, 6, 7, 9]
Output Array: [1, 2, 3, 4, 6, 7, 9]](https://image.slidesharecdn.com/selectionsort-171120131551/85/Selection-sort-11-320.jpg)
Selection sort
- 2. List of contents ● Introduction ● Example w/ illustrating figures ● Algorithm ● implementation (Java, C++, Python) ● Performance Runtime ○ Best, Average and worst cases. ● Execution ● Other Notes
- 3. Introduction ● sorts an array by repeatedly finding the minimum element (considering ascending order) from unsorted part and putting it at the beginning . ● The algorithm maintains two subarrays in a given array. 1) The subarray which is already sorted. 2) Remaining subarray which is unsorted. ● In every iteration ,the minimum element (considering ascending order) from the unsorted subarray is picked and moved to the sorted subarray .
- 4. Example arr[] = 19, 5, 7, 12 // Find the minimum element in arr[0...3] // and place it at beginning 5, 19, 7, 12 // Find the minimum element in arr[1...3] // and place it at beginning of arr[1...3] 5, 7, 19, 12 // Find the minimum element in arr[2...3] // and place it at beginning of arr[2...3] 5, 7, 12, 19
- 5. Algorithm . ● Let the min : 0 ● Search the minimum ● Swap with value at location min ● Increment min ● Repeat until is sorted
- 7. C++ . void selectionSort(int a[], int len) { int min, i, j ; for(i=0; i<len-1; i++) { min = i ; for(j=i+1; j<len; j++) { if(a[j] < a[min]) min = j ; } swap(&a[i], &a[min]) ; } }
- 8. JAVA . void sort(int a[]) { int len = a.length, min; for (int i = 0; i < len-1; i++) { min = i; for (int j=i+1; j<len; j++) if (a[j] < a[min]) min = j; int temp = a[min]; a[min] = a[i]; a[i] = temp; } }
- 9. Python . def selectionSort(a): for i in range(len(a)): min = i for j in range(i+1, len(a)): if a[min] > a[j]: min = j a[i], a[min] = a[min], a[i]
- 10. Performance Runtime ● Time complexity Θ(n2 ) . ● it never makes more than O(n) swaps => can be useful when memory write is a costly operation .
- 11. Execution . Input array : [4, 6, 3, 2, 1, 9, 7] Swap => 4, 1 First Action : [1, 6, 3, 2, 4, 9, 7] Swap => 6, 2 Second Action : [1, 2, 3, 6, 4, 9, 7] Swap => 6, 4 Fourth Action : [1, 2, 3, 4, 6, 9, 7] Swap => 9, 7 Sixth Action : [1, 2, 3, 4, 6, 7, 9] Output Array: [1, 2, 3, 4, 6, 7, 9]
- 12. Other Notes . ● Algorithmic Paradigm: Incremental Approach ● Sorting In Place: Yes ● Stable: Yes ● Online: Yes