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KOTLIN - SELECTION SORT CODE




Example :



class Sort {

    fun selectionSort(arr: Array<Int>) {

        var n = arr.size;
        var currentMaximum: Int;
        var temp: Int;

        for (i in 0..(n-1)) {

            currentMaximum = 0;

            // Considering the first element to be the maximum element of the unsorted array.
            // And, (n-i) is to ignore the comparisons that is already done.

            for(j in 1..(n-i-1)) {

                if (arr[j] > arr[currentMaximum]) {

                    currentMaximum = j;
                }
            }
            // Swap the Current Maximum element with the last element.

            temp = arr[n-i-1];
            arr[n-i-1] = arr[currentMaximum];
            arr[currentMaximum] = temp;
        }
    }
}


fun main(args: Array<String>) {
    var arr = arrayOf(7, 4, 8, 1, 6);

    var sort = Sort();
    sort.selectionSort(arr);

    for(i in 0..(arr.size-1)) {
        print("${arr[i]}, ");
    }
}


Output :



  1, 4, 6, 7, 8,

We are just concerned about the fun selectionSort(arr: Array<Int>) method, where the sorting logic is defined.


We have the array


var arr = arrayOf(7, 4, 8, 1, 6);

Which we have passed to the selectionSort(..) method.


In the bubbleSort(..) method, we have taken the count of the elements of the array.


var n = arr.size;

Also note that,


var currentMaximum: Int;

currentMaximum is going to hold the position of the Current Maximum value. I will clear it below.


Now, let us corelate this code with the explanation of Selection Sort.


Let us take the same values defined above.

java_Collections

And take the chunk of code and explain it.


	for (i in 0..(n-1)) {

		currentMaximum = 0;

		// Considering the first element to be the maximum element of the unsorted array.
		// And, (n-i) is to ignore the comparisons that is already done.

		for(j in 1..(n-i-1)) {

			if (arr[j] > arr[currentMaximum]) {

				currentMaximum = j;
			}
		}
		// Swap the Current Maximum element with the last element.

		temp = arr[n-i-1];
		arr[n-i-1] = arr[currentMaximum];
		arr[currentMaximum] = temp;
	}

So, the outer loop, i.e.


for (i in 0..(n-1))

Determines the Passes. If you see the above explanation you can find the first pass,


1st Pass (i.e. When i=0)


In the next step we have initialized the currentMaximum to 0.


currentMaximum = 0;

Because no matter what we have to initialize the currentMaximum to 0 at the end of every pass.


Then comes the the inner loop, i.e.


for(j in 1..(n-i-1))

Which determines the iterations.

java_Collections

Next, comes the comparison part where we compare 2nd element with the currentMaximum. Now, since currentMaximum is at the 0th position of the Array. We compare if 4 is greater than 7 or not.


if (arr[j] > arr[currentMaximum]) {

	currentMaximum = j;
}

Let, us also look at the 2nd iteration.

java_Collections

In the above diagram we can see that j is 2. And if we refer to the code,


if (arr[j] > arr[currentMaximum]) {

	currentMaximum = j;
}

a[j] is 8 and arr[currentMaximum] is 7. And 8 is greater than 7. So, we initialize currentMaximum with 2.

java_Collections

And in the next iteration j is increased by 1 and refers to the 3 in array,

java_Collections

In the next iteration j is increased by 1. And when we reach at the end of the pass(i.e. When j becomes 4),

java_Collections

We swap the currentMaximum with the last element.


temp = arr[n-i-1]; // (n-i-1) is (5-0-1) i.e. 4
arr[n-i-1] = arr[currentMaximum]; // currentMaximum is 2
arr[currentMaximum] = temp;

So, as mentioned we swap arr[n-i-1] 1.e. arr[2] with arr[currentMaximum] i.e. arr[4]

java_Collections

And continue in the same pattern.


Note : (n-i-1) in the conditional part of inner loop ignores the last element from each passes.

Efficiency / Running time of Selection Sort


If we consider the Selection Sort Algorithm, there are two loops. Firstly, there is the for loop. And inside the for loop there is also a for loop.


The for loop executes n times(Assuming the array contains n elements).


Now, for each iteration of for loop, the nested for loop also executes approximately n times.


Which means for 1st iteration of for loop,


the nested for loop also runs n time.

Similarly, for 2nd iteration of for loop,


inner for loop runs (n-1) times.

Similarly, for nth iteration of for loop,


inner for loop runs 1 time.

So, the running time is close to n*n or n^2.


So, in worst case the running time is O(n^2).


Note : Worst case is the scenario where the array elements are all sorted in descending order. i.e. 8, 7, 6, 4, 1.