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Everyday data structures

Everyday data structures

By : William Smith
Buy this Book
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Everyday data structures

Everyday data structures

By: William Smith
Buy this Book

Overview of this book

Explore a new world of data structures and their applications easily with this data structures book. Written by software expert William Smith, you?ll learn how to master basic and advanced data structure concepts. ? Fully understand data structures using Java, C and other common languages ? Work through practical examples and learn real-world applications ? Get to grips with data structure problem solving using case studies
Table of Contents (14 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Data Types: Foundational Structures
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1. Data Types: Foundational Structures
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Numeric data types
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Boolean data type
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Strings
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Summary
2
2. Arrays: Foundational Collections
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2. Arrays: Foundational Collections
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Mutable versus immutable arrays
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Advanced topics
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Summary
3
3. Lists: Linear Collections
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3. Lists: Linear Collections
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List implementations
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Instantiating lists
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Revisiting users logged in to a service
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Doubly linked list
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Searching
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A few pointers
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Summary
4
4. Stacks: LIFO Collections
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4. Stacks: LIFO Collections
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Initializing stacks
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Case study: motion planning algorithm
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Advanced topics - stack implementations
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Summary
5
5. Queues: FIFO Collections
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5. Queues: FIFO Collections
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Initializing queues
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Case study: customer service
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Advanced topics
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Summary
6
6. Dictionaries: Keyed Collections
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6. Dictionaries: Keyed Collections
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Initializing dictionaries
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Case study: arcade ticket totals
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Advanced topics
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Summary
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7. Sets: No Duplicates
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7. Sets: No Duplicates
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Set theory
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Initializing sets
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Example: revisiting users logged in to a service
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Case-study: music playlists
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Advanced topics
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Summary
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8. Structs: Complex Types
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8. Structs: Complex Types
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The essentials
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Enums
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Summary
9
9. Trees: Non-Linear Structures
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9. Trees: Non-Linear Structures
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Tree data structure versus tree data type
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Tree terminology
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Common operations
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Instantiating trees
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Tree structures
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Recursion
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Traversal
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Summary
10
10. Heaps: Ordered Trees
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10. Heaps: Ordered Trees
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Heap implementations
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Heap operations
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Instantiating heaps
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Min heap structure
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Common applications
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Summary
11
11. Graphs: Values with Relationships
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11. Graphs: Values with Relationships
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Visual graph concepts
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Graph operations
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Graph implementations
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The graph data structure
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Summary
12
12. Sorting: Bringing Order Out Of Chaos
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12. Sorting: Bringing Order Out Of Chaos
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Selection sort
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Insertion sort
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Bubble sort
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Quick sort
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Merge sort
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Bucket sort
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Summary
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13. Searching: Finding What You Need
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13. Searching: Finding What You Need
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Linear search
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Binary search
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Jump search
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Summary

Advanced topics

Now that we have examined how dictionaries are used in common applications, we should take some time to examine how dictionaries are implemented under the hood. The majority of dictionaries come in two distinct flavors: hash table based and search tree based. Although the mechanics of the two approaches are similar, and they typically share many of the same methods and functionality, the inner workings and ideal applications for each type are very different.

Hash table based dictionaries

The most common implementation of a dictionary is the hash table based associative array. When properly implemented, the hash table approach is extremely efficient and allows for O(1) complexity searches, inserts, and deletes. In each of the languages we are examining, the basic dictionary classes are based on hash tables by default. The general concept of a hash table based dictionary is that mapping for a specified key is stored at an index of an array, where the index is obtained by applying...

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Tech Concepts
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Programming languages
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