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Learning Functional Data Structures and Algorithms

You're reading from   Learning Functional Data Structures and Algorithms Learn functional data structures and algorithms for your applications and bring their benefits to your work now

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781785888731
Length 318 pages
Edition 1st Edition
Languages
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Authors (2):
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Raju Kumar Mishra Raju Kumar Mishra
Author Profile Icon Raju Kumar Mishra
Raju Kumar Mishra
Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Table of Contents (14) Chapters Close

Preface 1. Why Functional Programming? 2. Building Blocks FREE CHAPTER 3. Lists 4. Binary Trees 5. More List Algorithms 6. Graph Algorithms 7. Random Access Lists 8. Queues 9. Streams, Laziness, and Algorithms 10. Being Lazy - Queues and Deques 11. Red-Black Trees 12. Binomial Heaps 13. Sorting

Merge sort

Merge sort uses the divide and conquer philosophy. There will be a function split that will split a sequential data structure into two parts in such a way that the number of elements in the two split parts will differ by one element at the maximum. The split daughter lists, after merging, return the permutation of the original list.

Merge sort steps can be laid out in the following fashion:

  1. The sequence is split till every subsequence has at most one element.
  2. Every subsequence is merged in such a way that the merged sequence is sorted too.

No worries, we will discuss all the steps in detail in the following pages. Let's start with the split.

Splitting the sequence

The following diagram explains the splitting of a sequence:

Splitting the sequence

We start our sequence as [1, 3, 5, 2, 6]. In order to split it into two parts, we will fetch two elements (they are 1 and 3 for us) and put them as two subsequences, ss1 and ss2, respectively. Similarly, the next time, 5 and 2 will be taken and added to...

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