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Merge sort is also one of the 'divide & conquer' classes of algorithms. The fundamental idea in it is to split the list in a number of sublists, sort each of these sublists & merge them to get a single sorted list. The descriptive implementation of 2 way merge sort sees the input initially as n lists of size 1. These are merged to acquire n/2 lists of size
2. These n/2 lists are merged pair wise and so on until a single list is obtained. It can be better understood by the following instance. This is also called Concatenate sort. Figure 2 illustrate 2-way merge sort.
Merge sort is the best method for sorting linked lists within random order. The total computing time is of the 0(n log2n ).
The drawback of using mergesort is that it requires two arrays of the similar size & space for the merge phase. That is, to sort a list of size n, it requires space for 2n elements.
Figure: 2-way .merge sort
Mergesort is the greatest method for sorting linked lists into random order. The total computing time is of the 0(n log2n ).
The drawback of using mergesort is that it needs two arrays of the similar size and space for the merge phase. That is, to sort a list of size n, it requires space for 2n elements.
The complexity Ladder: T(n) = O(1). It is called constant growth. T(n) does not raise at all as a function of n, it is a constant. For illustration, array access has this c
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