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Everyday data structures

Everyday data structures

By : Smith
Buy this Book
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Everyday data structures

Everyday data structures

By: 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
7
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
8
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

Set theory

The concept of a set is relatively simple, but in practice a concrete implementation can be somewhat difficult to understand due to its mathematical origins. Therefore, in order to fully appreciate the set data structure, it becomes necessary to examine some of the characteristics and functions of set theory upon which the set data structure is built. Set theory is a branch of mathematics that studies collections, or sets, of objects. Although set theory is a major area of research in mathematics with many interrelated sub-fields, we really only need to examine five functions for combining and relating sets to one another to understand the set data structure:

  • Union: A union is one of the fundamental methods of combining and relating sets to one another. A union of a series of n sets is the set of only those distinct elements contained in those sets. This means that, if you combine sets A and B, the resulting set will only contain unique elements from set A and B. If an element...

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Tech Concepts
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Programming languages
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