JavaScript Data Structures and Algorithms An Introduction to Understanding and Implementing Core Data Structure and Algorithm Fundamentals 1st Editon by Sammie Bae ISBN 1484239873 9781484239872

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Product details:

ISBN 10: 1484239873  
ISBN 13: 9781484239872
Author: Sammie Bae

Explore data structures and algorithm concepts and their relation to everyday JavaScript development. A basic understanding of these ideas is essential to any JavaScript developer wishing to analyze and build great software solutions.

You’ll discover how to implement data structures such as hash tables, linked lists, stacks, queues, trees, and graphs. You’ll also learn how a URL shortener, such as bit.ly, is developed and what is happening to the data as a PDF is uploaded to a webpage. This book covers the practical applications of data structures and algorithms to encryption, searching, sorting, and pattern matching.

It is crucial for JavaScript developers to understand how data structures work and how to design algorithms. This book and the accompanying code provide that essential foundation for doing so. With JavaScript Data Structures and Algorithms you canstart developing your knowledge and applying it to your JavaScript projects today.

What You’ll Learn

• Review core data structure fundamentals: arrays, linked-lists, trees, heaps, graphs, and hash-table
• Review core algorithm fundamentals: search, sort, recursion, breadth/depth first search, dynamic programming, bitwise operators
  
• Examine how the core data structure and algorithms knowledge fits into context of JavaScript explained using prototypical inheritance and native JavaScript objects/data types
  
• Take a high-level look at commonly used design patterns in JavaScript
  

Who This Book Is For

Existing web developers and software engineers seeking to develop or revisit their fundamental data structures knowledge; beginners and students studying JavaScript independently or via a course or coding bootcamp.

JavaScript Data Structures and Algorithms An Introduction to Understanding and Implementing Core Data Structure and Algorithm Fundamentals 1st Table of contents:

• JavaScript Fundamentals

  • Overview of JavaScript Basics
  • Functions, Objects, and Arrays
  • Understanding JavaScript Data Types
  • JavaScript’s Built-In Methods and Properties

• Big O Notation

  • What is Big O Notation?
  • Analyzing Algorithm Efficiency
  • Time Complexity and Space Complexity
  • Examples of Common Time Complexities

• Arrays and Lists

  • Introduction to Arrays
  • Array Operations (Insertion, Deletion, Search)
  • Resizing Arrays
  • Multidimensional Arrays
  • Linked Lists (Singly, Doubly Linked Lists)

• Stacks and Queues

  • Introduction to Stacks
  • Stack Operations (Push, Pop)
  • Queues: Basic Concept and Operations
  • Implementing Stacks and Queues in JavaScript
  • Real-World Applications of Stacks and Queues

• Hash Tables

  • Introduction to Hash Tables
  • Understanding Hash Functions
  • Collision Resolution
  • Hash Table Operations (Insertion, Deletion, Search)
  • Implementing Hash Tables in JavaScript

• Trees

  • Introduction to Trees and Tree Terminology
  • Binary Trees: Structure and Operations
  • Binary Search Trees (BST)
  • AVL Trees and Self-Balancing Trees
  • Tree Traversal (Preorder, Inorder, Postorder, Level Order)
  • Implementing Trees in JavaScript

• Heaps

  • Introduction to Heaps
  • Min-Heaps vs. Max-Heaps
  • Heap Operations (Insertion, Deletion)
  • Heap Sort Algorithm
  • Implementing Heaps in JavaScript

• Graphs

  • Introduction to Graphs and Graph Terminology
  • Graph Representations (Adjacency List, Adjacency Matrix)
  • Graph Traversals (BFS, DFS)
  • Directed vs. Undirected Graphs
  • Weighted Graphs and Shortest Path Algorithms
  • Implementing Graphs in JavaScript

• Sorting Algorithms

  • Introduction to Sorting
  • Selection Sort
  • Bubble Sort
  • Insertion Sort
  • Merge Sort
  • Quick Sort
  • Comparison of Sorting Algorithms

• Searching Algorithms

  • Linear Search
  • Binary Search
  • Hashing for Searching
  • Search Tree Operations

• Dynamic Programming

  • Introduction to Dynamic Programming
  • Memoization vs. Tabulation
  • Classic DP Problems (Fibonacci, Knapsack Problem, etc.)
  • Implementing Dynamic Programming in JavaScript

• Greedy Algorithms

  • Introduction to Greedy Algorithms
  • Greedy Algorithm Approach
  • Classic Greedy Problems (Coin Change Problem, Activity Selection)
  • Implementing Greedy Algorithms in JavaScript

• Backtracking Algorithms

  • Introduction to Backtracking
  • Solving Problems Using Backtracking
  • Classic Backtracking Problems (N-Queens Problem, Subset Sum Problem)

• Graph Algorithms

  • Dijkstra’s Algorithm for Shortest Path
  • Floyd-Warshall Algorithm
  • Topological Sort
  • Bellman-Ford Algorithm
  • Floyd-Warshall Algorithm for All Pair Shortest Paths

• Advanced Data Structures

  • Tries
  • B-Trees and B+ Trees
  • Segment Trees
  • Bloom Filters

• Problem Solving and Interview Preparation

  • Common Coding Interview Problems
  • Tips for Preparing for Algorithmic Interviews
  • Practice Problems and Solutions

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