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Everyday data structures

You're reading from   Everyday data structures A practical guide to learning data structures simply and easily

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787121041
Length 344 pages
Edition 1st Edition
Languages
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Author (1):
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 Smith Smith
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Smith
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Table of Contents (20) Chapters Close

Everyday Data Structures
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Preface
1. Data Types: Foundational Structures FREE CHAPTER 2. Arrays: Foundational Collections 3. Lists: Linear Collections 4. Stacks: LIFO Collections 5. Queues: FIFO Collections 6. Dictionaries: Keyed Collections 7. Sets: No Duplicates 8. Structs: Complex Types 9. Trees: Non-Linear Structures 10. Heaps: Ordered Trees 11. Graphs: Values with Relationships 12. Sorting: Bringing Order Out Of Chaos 13. Searching: Finding What You Need

Tree terminology


Many of the terms and definitions used in trees are unique to these data structures. Therefore, before we can examine tree data structures we need to take the time to learn the language.

Here are some of the most common and important terms:

  • Node: Any object or value stored in the tree represents a node. In the preceding figure, the root and all of its children and descendants are independent nodes.

  • Root: The root is the base node of the tree. Ironically, this node is typically depicted at the top of a graphic representation of the tree. Note that a root node, even if it has zero descendants, represents an entire tree by itself.

  • Parent: A parent node is any node which contains 1...n child nodes. The parent is only the parent in respect to one of its children. Also note that any parent node can have 0...n children depending on the rules associated with the tree's structure.

  • Child: Any node other than the root node is a child to one (and only one) other node. The root node of any...

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