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lecture16 - COMP 250 Winter 2010 16 mergesort Example 7...

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COMP 250 Winter 2010 16 - mergesort Feb 12, 2010 Example 7: Mergesort In lecture 3, we saw the “insertion sort” algorithm for sorting n items. This algorithm was O ( n 2 ) and we saw that, in the worst case that the input elements are sorted in the wrong order, the algorithm requires n ( n - 1) 2 or n 2 2 n 2 or operations. Thus, not only is insertion sort O ( n 2 ), it is also Ω( n 2 ) – see Exercises 2. There are sorting algorithms run in time less than O ( n 2 ), even in the worst case that the input elements are sorted but in the wrong order. Today we will see one them, called mergesort . The idea of mergesort is simple. If there is just one number to sort ( n = 1), then do nothing. Otherwise, partition the list of n elements into two lists of size n/ 2 and n/ 2 , sort each of these two lists, and then merge the two sorted lists. The ±oor and ceiling notation is used for the case that n is odd, and so the two sets are of di²erent sizes (even and odd). For example, suppose we have a list 8 , 10 , 3 , 11 , 6 , 1 , 9 , 7 , 13 , 2 , 5 , 4 , 12 . We partition it into two lists < 8 , 10 , 3 , 11 , 6 , 1 , 8 > < 9 , 7 , 13 , 2 , 5 , 4 , 12 > . and sort these (by applying mergesort recursively): < 1 , 3 , 6 , 8 , 10 , 11 > < 2 , 4 , 5 , 7 , 9 , 12 , 13 > . Then, we merge these two lists
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This note was uploaded on 09/25/2011 for the course COMP 250 taught by Professor Blanchette during the Spring '08 term at McGill.

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lecture16 - COMP 250 Winter 2010 16 mergesort Example 7...

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