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Data Structures and Algorithms explained and implemented in JavaScript

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Rashad919/dsa.js-data-structures-algorithms-javascript

 
 

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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 algorithmssee.

Book

You can check out thedsa.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.

dsajs algorithms javascript book

Data Structures

We are covering the following data structures.

Interactive Data Structures

Linear Data Structures

  1. Arrays: Built-in in most languages so not implemented here.Array Time complexity

  2. Linked Lists: each data node has a link to the next (andprevious).Code|Linked List Time Complexity

  3. Queue: data flows in a "first-in, first-out" (FIFO) manner.Code|Queue Time Complexity

  4. Stacks: data flows in a "last-in, first-out" (LIFO) manner.Code|Stack Time Complexity

Non-Linear Data Structures

  1. Trees: data nodes has zero or more adjacent nodes a.k.a.children. Each node can only have one parent node otherwise is agraph not a tree.Code|Docs

    1. Binary Trees: same as tree but only can have two children atmost.Code|Docs

    2. Binary Search Trees (BST): same as binary tree, but thenodes value keep this orderleft < parent < right.Code|BST Time complexity

    3. AVL Trees: Self-balanced BST to maximize look up time.Code|AVL Tree docs|Self-balancing & tree rotations docs

    4. Red-Black Trees: Self-balanced BST more loose than AVL tomaximize insertion speed.Code

  2. Maps: key-value store.

    1. Hash Maps: implements map using a hash function.Code|HashMap time complexity

    2. Tree Maps: implement map using a self-balanced BST.Code|TreeMap docs|TreeMap time complexity

  3. Graphs: datanodes that can have a connection oredge tozero or more adjacent nodes. Unlike trees, nodes can have multipleparents, loops.Code|Graph Time Complexity

Algorithms

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