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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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William Smith William Smith
Author Profile Icon William Smith
William Smith
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Table of Contents (14) Chapters Close

Preface 1. Data Types: Foundational Structures 2. Arrays: Foundational Collections FREE CHAPTER 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

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Now that we have examined how sets are used in common applications, we should take some time to examine how they are implemented under the hood. The majority of sets come in three varieties: hash table-based sets, tree-based sets, and array-based sets.

Hash table-based sets

Hash table-based sets are typically used for unordered collections of data. As such, the majority of sets you will encounter for non-specialized applications will be hash table-based. Hash table-based sets share similar operational costs with dictionaries. For example, search, insert, and delete operations all have an operational cost of O(n).

Tree-based sets

Tree-based sets are typically based on binary search trees, but they sometimes can be based on other structures. Due to their design, the binary search tree allows for very efficient search functions on average, as each node that is examined can allow for branches of the tree to be discarded from the remaining search pattern. Although the worst case scenario...

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