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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? FREE CHAPTER 2. Building Blocks 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

Chapter 4.  Binary Trees

A tree is a data structure that simulates a hierarchical tree structure with a root node and children nodes. A child node can have children nodes of its own, thus realizing the hierarchy. Just like a list, a tree is defined recursively.

Binary Trees

A binary tree is a tree in which each node has zero, one, or at most two child nodes. See http://opendatastructures.org/ods-java/6_Binary_Trees.html for an excellent refresher on binary trees.

In this chapter, we will look at the functional implementation of binary trees. As in the previous chapter, we will not perform any in-place mutations. Any update operation will preserve the earlier version, thereby making it a persistent binary tree.

We will implement many common binary tree algorithms. After covering binary trees, we will look at Binary Search Trees.

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