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Data Structures and Algorithms in JavaScript

This repository covers the implementation of the classical algorithms and data structures in JavaScript.

Usage

You can clone the repo or install the code from NPM:

npm install dsa.js

and then you can import it into your programs or CLI

const { LinkedList, Queue, Stack } = require('dsa.js');

For a full list of all the exposed data structures and algorithms see.

Book

You can check out the dsa.js book that goes deeper into each topic and provide additional illustrations and explanations.

Algorithmic toolbox to avoid getting stuck while coding.
Explains data structures similarities and differences.
Algorithm analysis fundamentals (Big O notation, Time/Space complexity) and examples.
Time/space complexity cheatsheet.

WARNING: Although you can find the book text on this repo, there are some things that doesn't work well with Github's Asciidoc unfortunately. For instance rendering Graphviz diagrams, internal link references, including referenced chunks of code within text and some so on. For better reading experience and nicer presentation you can get the PDF format here.

Data Structures

We are covering the following data structures.

Linear Data Structures

Arrays: Built-in in most languages so not implemented here. Post.
Linked Lists: each data node has a link to the next (and previous). Code | Post.
Queue: data flows in a "first-in, first-out" (FIFO) manner. Code | Post
Stacks: data flows in a "last-in, first-out" (LIFO) manner. Code | Post.

Non-Linear Data Structures

Trees: data nodes has zero or more adjacent nodes a.k.a. children. Each node can only have one parent node otherwise is a graph not a tree. Code | Post
1. Binary Trees: same as tree but only can have two children at most. Code | Post
2. Binary Search Trees (BST): same as binary tree, but the nodes value keep this order left < parent < rigth. Code | Post
3. AVL Trees: Self-balanced BST to maximize look up time. Code | Post
4. Red-Black Trees: Self-balanced BST more loose than AVL to maximize insertion speed. Code
Maps: key-value store.
1. Hash Maps: implements map using a hash function. Code | Post
2. Tree Maps: implement map using a self-balanced BST. Code
Graphs: data nodes that can have a connection or edge to zero or more adjacent nodes. Unlike trees, nodes can have multiple parents, loops. Code | Post

Algorithms

Sorting algorithms
- Bubble Sort. Code
- Insertion Sort. Code
- Selection Sort. Code
- Merge Sort. Code
- Quick sort. Code
Greedy Algorithms
- Fractional Knapsack Problem. Code
Divide and Conquer
- Fibonacci Numbers. Code
Dynamic Programming
- Fibonacci with memoization. Code
Backtracking algorithms
- Word permutations. Code