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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

Red-Black trees

Given this rotation algorithm, we can now look at the core Red-Black tree.

A Red-Black tree node always has a color, either red or black, with the following invariants:

  • A red node can never have a red child
  • Every path from the root to an empty node contains the same number of black nodes

An empty node is a leaf nil node. This nil node indicates termination and is also known as a sentinel node.

Here is an example of a Red-Black tree. Note that each node is annotated with its black height. The black height is the number of black nodes from the node to the leaf.

Note these important points:

  1. The root is always black.
  2. Every leaf is black.
  3. Both the children of a red node are black (as a red node cannot have a red child).
  4. Every path from a node to a leaf contains the same number of black nodes.

The following diagram shows a Red-Black tree:

Red-Black trees

Take each of the invariants from earlier and check whether the tree satisfies each one of them.

When we look at rebalancing, we will see how the first...

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