In this post, we will talk about different Classification of Sorting Algorithms.
Classification of Sorting Algorithms:
By Number of Comparisons
In this method, Sorting algorithms are usually classified based on the number of comparisons. For comparison-based sorting algorithms best-case behavior is O(n log n) and worst-case behavior is O(n2). Comparison-based sorting algorithms evaluate the elements of the list by key comparison operation and need at least O(n log n) comparisons for most inputs.
By Number of Swaps
In this method, sorting algorithms are categorized by the number of swaps.
By Memory Usage
Some sorting algorithms are ”in place” and they need O(1) or O(n log n) memory to create auxiliary locations for sorting the data temporarily.
Sorting algorithms are either recursive(Quicksort) or non-recursive(selection Sort and Insertion sort) and there are some algorithms that use both(merge sort).
Sorting algorithms is stable if for all the indices i and j such that the key A[i] equals key A[j], If record R[i] precedes record R[j] in the original input. Record R[i] precedes record R[j] in the sorted list. Few sorting algorithms maintain the relative order of elements with equal keys(equivalent elements retain their relative positions even after sorting)
With a few sorting algorithms the complexity changes based on pre-sortedness (quicksort). pre-sortedness of the input affects the running time. Algorithms that take this into account are usually known to be adaptive.
Sorting algorithms that use the main memory exclusively during the sorting are called internal sorting algorithms. This kind of algorithm usually assumes high-speed random access to all memory.
Sorting algorithms which use external memory, such as disk or tape, during the Sort comes under this category
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That’s all about Classification of Sorting Algorithms
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