Examples of using Merge sort in English and their translations into Romanian
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So that's Merge Sort in a picture.
So those are the reasons to start out with Merge Sort.
So the Merge Sort is its purpose in life is to sort the given input array.
So what is the computational problem that Merge Sort is meant to solve?
So for example, Merge Sort was certainly known, to John Von Neumann all the way back in 1945.
We will see two examples when we look at merge sort and quick sort. .
Now another reason I want to discuss Merge Sort is that our analysis of it will naturally segment discussion of how we analyze the algorithms in this course and in general.
So hopefully, I don't know, it may not be easy the analysis of Merge Sort discussion.
Finally, we will do the analysis of Merge Sort using what's called as"Recursion-Tree" method.
Probably you know some number of sorting algorithms perhaps including Merge Sort itself.
And I will leave it as an exercise which I encourage you to do, which is to think about how the Merge Sort algorithm implementation and analysis would be different, if at all, if there were ties.
And we will do that by first of all reviewinga famous sorting algorithm, namely the Merge Sort algorithm.
So in particular, when I describe the Merge Sort algorithm, you will notice that I'm not going to describe in a level of detail that you can just translate it line by line into a working program in some programming language.
So the second reason that I wanna start out by talking about the Merge Sort algorithm, is to help you calibrate your preparation.
And Merge Sort is better than a lot of this sort of simpler, I would say obvious,sorting algorithms,… so for example, three other sorting algorithms that you may know about, but that I'm not going to discuss here.
So we will get a win,first sorting in Divide-and-Conquer, and Merge Sort is the algorithm that realizes that benefit.
Merge sort algorithms typically require a time approximately proportional to N· log(N).[79] The base of the logarithm is not specified here, because the result only changes by a constant factor when another base is used.
One, I haven't even putdown on the slide, which is like a number of the algorithms we will see,"Merge Sort" as an oldie but a goodie.
Again I just say this to jog your memory,these are simpler sorts than Merge Sort,… but all of them are worse in the sense that they're lack in performance in general, which scales with N^2,… and the input array has N elements, so they all have, in some sense, quadratic running time.
And then giving a really fairly mathematically precise upper bound on exactly how many operations the Merge Sort algorithm requires to correctly sort an input array.
This algorithm requires, on average, log2(N) comparisons, where N is the list's length.[78]Similarly, the merge sort algorithm sorts an unsorted list by dividing the list into halves and sorting these first before merging the results.
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