Join Raghavendra Dixit for an in-depth discussion in this video Time complexity of merge sort, part of Introduction to Data Structures & Algorithms in Java.
- Now let's see how much time…does the Merge Sort Algorithm take.…Rather is it good or bad compared to the other sorting…algorithms that we learned earlier like Insertion Sort.…So how do we get an estimate of time?…In this algorithm the array is logically broken down…into smaller parts, right?…So let's say that this is the height of the top recursion.…And we can say that each of the breaking up steps…creates a layer kind of, okay?…So we will generate "H" layers…from the full recursion, alright?…Now in each of the horizontal layers…how many comparisons are made?…Well there are N elements entirely…hence we will end up making "N" comparisons.…
And with all the copying of elements in each layer…the number of operations will be proportional to "N"…And because there are "H" layers…hence the total number of operations must be…some function of "H" times "N", right?…So all we need to do now is…find the height or depth of recursion.…So let's do that now.…Let's see how many logical arrays do we have in each layer?…In layer one, how many arrays do you see?…
Note: This course was created by Packt Publishing. We are pleased to host this training in our library.
- Why study data structures and algorithms?
- How to calculate the time complexity
- Using Big O notation
- Using basic sorting and search algorithms
- Searching elements in unordered arrays and ordered arrays
- Implementing a linked list in Java
- Implementing stacks using arrays
- Queues using arrays
- Binary search trees
- Representing heaps using arrays
Skill Level Intermediate
1. Introduction to Algorithms
2. Analysis of Algorithms
3. Basic Sorting and Search Algorithms
4. Linked Lists
5. Stacks and Queues
7. Binary Search Trees
8. More Sorting Algorithms
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