5.11. The Merge Sort¶
We now turn our attention to using a divide and conquer strategy as a
way to improve the performance of sorting algorithms. The first
algorithm we will study is the merge sort. Merge sort is a recursive
algorithm that continually splits a list in half. If the list is empty
or has one item, it is sorted by definition (the base case). If the list
has more than one item, we split the list and recursively invoke a merge
sort on both halves. Once the two halves are sorted, the fundamental
operation, called a merge, is performed. Merging is the process of
taking two smaller sorted lists and combining them together into a
single, sorted, new list. Figure 10 shows our familiar example
list as it is being split by
mergeSort. Figure 11 shows
the simple lists, now sorted, as they are merged back together.
mergeSort function shown in ActiveCode 1 begins by asking the
base case question. If the length of the list is less than or equal to
one, then we already have a sorted list and no more processing is
necessary. If, on the other hand, the length is greater than one, then
we use the Python
slice operation to extract the left and right
halves. It is important to note that the list may not have an even
number of items. That does not matter, as the lengths will differ by at
mergeSort function is invoked on the left half and the
right half (lines 8–9), it is assumed they are sorted. The rest of the
function (lines 11–31) is responsible for merging the two smaller sorted
lists into a larger sorted list. Notice that the merge operation places
the items back into the original list (
alist) one at a time by
repeatedly taking the smallest item from the sorted lists.
mergeSort function has been augmented with a
In order to analyze the
mergeSort function, we need to consider the
two distinct processes that make up its implementation. First, the list
is split into halves. We already computed (in a binary search) that we
can divide a list in half \(\log n\) times where n is the
length of the list. The second process is the merge. Each item in the
list will eventually be processed and placed on the sorted list. So the
merge operation which results in a list of size n requires n
operations. The result of this analysis is that \(\log n\) splits,
each of which costs \(n\) for a total of \(n\log n\)
operations. A merge sort is an \(O(n\log n)\) algorithm.
Recall that the slicing operator is \(O(k)\) where k is the size
of the slice. In order to guarantee that
mergeSort will be
\(O(n\log n)\) we will need to remove the slice operator. Again,
this is possible if we simply pass the starting and ending indices along
with the list when we make the recursive call. We leave this as an
It is important to notice that the
mergeSort function requires extra
space to hold the two halves as they are extracted with the slicing
operations. This additional space can be a critical factor if the list
is large and can make this sort problematic when working on large data
Q-17: Given the following list of numbers: <br> [21, 1, 26, 45, 29, 28, 2, 9, 16, 49, 39, 27, 43, 34, 46, 40] <br> which answer illustrates the list to be sorted after 3 recursive calls to mergesort?
- (A) [16, 49, 39, 27, 43, 34, 46, 40]
- This is the second half of the list.
- (B) [21,1]
- Yes, mergesort will continue to recursively move toward the beginning of the list until it hits a base case.
- (C) [21, 1, 26, 45]
- Remember mergesort doesn't work on the right half of the list until the left half is completely sorted.
- (D) 
- This is the list after 4 recursive calls
Q-18: Given the following list of numbers: <br> [21, 1, 26, 45, 29, 28, 2, 9, 16, 49, 39, 27, 43, 34, 46, 40] <br> which answer illustrates the first two lists to be merged?
- (A) [21, 1] and [26, 45]
- The first two lists merged will be base case lists, we have not yet reached a base case.
- (B) [[1, 2, 9, 21, 26, 28, 29, 45] and [16, 27, 34, 39, 40, 43, 46, 49]
- These will be the last two lists merged
- (C)  and 
- The lists  and  are the first two base cases encountered by mergesort and will therefore be the first two lists merged.
- (D)  and 
- Although 9 and 16 are next to each other they are in different halves of the list starting with the first split.