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Insertion sort is a simple sorting algorithm that builds the final sorted array (or list) one item at a time by comparisons. It is much less efficient on large lists than more advanced algorithms such as quicksort, heapsort, or merge sort. However, insertion sort provides several advantages:
Insertion sort is widely used for small data sets, while for large data sets an asymptotically efficient sort is used, primarily heapsort, merge sort, or quicksort. Efficient implementations generally use a hybrid algorithm , combining an asymptotically efficient algorithm for the overall sort with insertion sort for small lists at the bottom ...
sort is a generic function in the C++ Standard Library for doing comparison sorting.The function originated in the Standard Template Library (STL).. The specific sorting algorithm is not mandated by the language standard and may vary across implementations, but the worst-case asymptotic complexity of the function is specified: a call to sort must perform no more than O(N log N) comparisons ...
And for further clarification check leet code problem number 88. As another example, many sorting algorithms rearrange arrays into sorted order in-place, including: bubble sort, comb sort, selection sort, insertion sort, heapsort, and Shell sort. These algorithms require only a few pointers, so their space complexity is O(log n). [1]
Introsort or introspective sort is a hybrid sorting algorithm that provides both fast average performance and (asymptotically) optimal worst-case performance. It begins with quicksort, it switches to heapsort when the recursion depth exceeds a level based on (the logarithm of) the number of elements being sorted and it switches to insertion sort when the number of elements is below some threshold.
Bucket sort can be seen as a generalization of counting sort; in fact, if each bucket has size 1 then bucket sort degenerates to counting sort. The variable bucket size of bucket sort allows it to use O( n ) memory instead of O( M ) memory, where M is the number of distinct values; in exchange, it gives up counting sort's O( n + M ) worst-case ...
If the number m of buckets is linear in the input size n, each bucket has a constant size, so sorting a single bucket with an O(n 2) algorithm like insertion sort has complexity O(1 2) = O(1). The running time of the final insertion sorts is therefore m ⋅ O(1) = O(m) = O(n).
In computer science, selection sort is an in-place comparison sorting algorithm.It has a O(n 2) time complexity, which makes it inefficient on large lists, and generally performs worse than the similar insertion sort.