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Swift Data Structure and Algorithms

You're reading from   Swift Data Structure and Algorithms Implement Swift structures and algorithms natively

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884504
Length 286 pages
Edition 1st Edition
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Author (1):
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Mario Eguiluz Alebicto Mario Eguiluz Alebicto
Author Profile Icon Mario Eguiluz Alebicto
Mario Eguiluz Alebicto
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Table of Contents (10) Chapters Close

Preface 1. Walking Across the Playground FREE CHAPTER 2. Working with Commonly Used Data Structures 3. Standing on the Shoulders of Giants 4. Sorting Algorithms 5. Seeing the Forest through the Tree 6. Advanced Searching Methods 7. Graph Algorithms 8. Performance and Algorithm Efficiency 9. Choosing the Perfect Algorithm

Trie tree

Until now, we have seen different types of trees, such as binary trees, binary search trees, red-black trees, and AVL trees. In all these types of tree, the content of a node (a value or a key) is not related to the content of a previous node. A single node has a complete meaning, such as a value or number by itself.

But in some scenarios in real life, we need to store a series of data in which those values have common parts; think of it as the suffixes or prefixes in related words, in the alphabet, in a telephone directory.

Here is where a trie tree shines. They are ordered data structures where edges contain part of a key and its descendant nodes have common share part of the previous values. Check this example out:

Trie tree

Trie tree example – storing the words plan, play, poll, post

As you can see in the previous figure, each edge of the tree contains part of a key, and by adding every edge key from the top to a specific node (or leaf), we can build a complete key.

Some...

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