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  • Book Overview & Buying Learning JavaScript Data Structures and Algorithms
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Learning JavaScript Data Structures and Algorithms

Learning JavaScript Data Structures and Algorithms

By : Loiane Avancini
4.3 (24)
Buy this Book
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Learning JavaScript Data Structures and Algorithms

Learning JavaScript Data Structures and Algorithms

4.3 (24)
By: Loiane Avancini
Buy this Book

Overview of this book

If you are a JavaScript developer or someone who has basic knowledge of JavaScript, and want to explore its optimum ability, this fast-paced book is definitely for you. Programming logic is the only thing you need to know to start having fun with algorithms.
Table of Contents (12 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. JavaScript – A Quick Overview
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1. JavaScript – A Quick Overview
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Setting up the environment
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JavaScript basics
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Control structures
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Functions
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Object-oriented programming
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Debugging and tools
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Summary
2
2. Arrays
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2. Arrays
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Why should we use arrays?
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Creating and initializing arrays
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Adding and removing elements
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Two-dimensional and multi-dimensional arrays
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References for JavaScript array methods
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Summary
3
3. Stacks
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3. Stacks
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Creating a stack
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Decimal to binary
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Summary
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4. Queues
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4. Queues
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Creating a queue
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The priority queue
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The circular queue – Hot Potato
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Summary
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5. Linked Lists
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5. Linked Lists
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Creating a linked list
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Doubly linked lists
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Circular linked lists
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Summary
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6. Sets
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6. Sets
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Creating a set
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Set operations
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Summary
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7. Dictionaries and Hashes
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7. Dictionaries and Hashes
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Dictionaries
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The hash table
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Summary
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8. Trees
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8. Trees
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Trees terminology
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Binary tree and binary search tree
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Tree traversal
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Searching for values in a tree
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More about binary trees
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Summary
9
9. Graphs
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9. Graphs
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Graph terminology
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Representing a graph
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Creating the Graph class
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Graph traversals
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Summary
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10. Sorting and Searching Algorithms
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10. Sorting and Searching Algorithms
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Sorting algorithms
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Searching algorithms
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Summary
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Index
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Index

Representing a graph

There are a few ways we can represent graphs when it comes to data structures. There is no correct way of representing a graph among the existing possibilities. It depends on the type of problem you need to resolve and the type of graph as well.

The adjacency matrix

The most common implementation is the adjacency matrix. Each node is associated with an integer, which is the array index. We represent the connectivity between vertices using a two-dimensional array, as array[i][j] === 1 if there is an edge from the node with index i to the node with index j; or as array[i][j] === 0 otherwise, as demonstrated by the following diagram:

Graphs that are not strongly connected (sparse graphs) will be represented by a matrix with many zero entries in the adjacency matrix. This means we will waste space in the computer memory to represent edges that do not exist; for example, if we need to find the adjacent vertices of a given vertex, we will have to iterate through the whole row...

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Tech Concepts
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Programming languages
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Learning JavaScript Data Structures and Algorithms
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