This repository contains JavaScript based examples of many popular algorithms and data structures.

Each algorithm and data structure has its own separate README with related explanations and links for further reading (including ones to YouTube videos).

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We’re writing a book that will clearly explain, in detail, the main algorithms. If you’d like to be notified when the “JavaScript Algorithms” book launches, click here.

A data structure is a particular way of organizing and storing data in a computer so that it can be accessed and modified efficiently. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.

B - Beginner, A - Advanced

• B Linked List
• B Doubly Linked List
• B Queue
• B Stack
• B Hash Table
• B Heap
• B Priority Queue
• A Trie
• A Tree
  • A Binary Search Tree
  • A AVL Tree
  • A Red-Black Tree
  • A Segment Tree - with min/max/sum range queries examples
  • A Fenwick Tree (Binary Indexed Tree)
• A Graph (both directed and undirected)
• A Disjoint Set
• A Bloom Filter

An algorithm is an unambiguous specification of how to solve a class of problems. It is a set of rules that precisely define a sequence of operations.

B - Beginner, A - Advanced

• Math
  • B Bit Manipulation - set/get/update/clear bits, multiplication/division by two, make negative etc.
  • B Factorial
  • B Fibonacci Number
  • B Primality Test (trial division method)
  • B Euclidean Algorithm - calculate the Greatest Common Divisor (GCD)
  • B Least Common Multiple (LCM)
  • B Sieve of Eratosthenes - finding all prime numbers up to any given limit
  • B Is Power of Two - check if the number is power of two (naive and bitwise algorithms)
  • B Pascal's Triangle
  • A Integer Partition
  • A Liu Hui π Algorithm - approximate π calculations based on N-gons
• Sets
  • B Cartesian Product - product of multiple sets
  • B Fisher–Yates Shuffle - random permutation of a finite sequence
  • A Power Set - all subsets of a set
  • A Permutations (with and without repetitions)
  • A Combinations (with and without repetitions)
  • A Longest Common Subsequence (LCS)
  • A Longest Increasing Subsequence
  • A Shortest Common Supersequence (SCS)
  • A Knapsack Problem - "0/1" and "Unbound" ones
  • A Maximum Subarray - "Brute Force" and "Dynamic Programming" (Kadane's) versions
  • A Combination Sum - find all combinations that form specific sum
• Strings
  • B Hamming Distance - number of positions at which the symbols are different
  • A Levenshtein Distance - minimum edit distance between two sequences
  • A Knuth–Morris–Pratt Algorithm (KMP Algorithm) - substring search (pattern matching)
  • A Z Algorithm - substring search (pattern matching)
  • A Rabin Karp Algorithm - substring search
  • A