How does the selection sort algorithm work?

Selection sort works by repeatedly finding the minimum element from the unsorted part and putting it at the beginning.

In more detail, selection sort is a simple comparison-based algorithm. It divides the input list into two parts: the sorted part at the left end and the unsorted part at the right end. Initially, the sorted part is empty and the unsorted part is the entire list. The algorithm proceeds by finding the smallest (or largest, depending on the sorting order) element in the unsorted sublist, swapping it with the leftmost unsorted element (putting it in sorted order), and moving the sublist boundaries one element to the right.

The key operation of the selection sort is the comparison of two elements. This is done in a loop that starts at the beginning of the unsorted part and goes through each element, comparing it to the current minimum. If a smaller element is found, it becomes the new minimum. Once the end of the list is reached, the minimum element is swapped with the first element of the unsorted part. This element is now considered sorted, and the process repeats for the rest of the list.

Selection sort is noted for its simplicity, and it has performance advantages over more complicated algorithms in certain situations, particularly where auxiliary memory is limited. However, it is not suitable for large datasets as its average and worst-case time complexities are of order O(n^2), where n is the number of items being sorted.

In terms of space complexity, selection sort is very efficient. It only uses a constant amount of additional space to hold the current minimum and its index, so the space complexity is O(1). This makes selection sort a good choice when memory space is a concern.

In conclusion, selection sort is a simple and intuitive sorting algorithm that works well for small lists or when memory is limited. However, its poor time complexity makes it less suitable for larger datasets.