# What ## Brief Javascript & TypeScript Data Structure collections. ## Algorithms DFS, DFSIterative, BFS, morris, Bellman-Ford Algorithm, Dijkstra's Algorithm, Floyd-Warshall Algorithm, Tarjan's Algorithm. Listed only a few out, you can discover more in API docs ## Code design By strictly adhering to object-oriented design (BinaryTree -> BST -> AVLTree -> TreeMultiset), you can seamlessly inherit the existing data structures to implement the customized ones you need. Object-oriented design stands as the optimal approach to data structure design. # How ## install ### npm ```bash npm install data-structure-typed ``` ### yarn ```bash yarn add data-structure-typed ``` ### CDN ```html ``` ```javascript const {AVLTree} = dataStructureTyped; const {Heap, MinHeap, SinglyLinkedList, Stack, AVLTreeNode, BST, Trie, DirectedGraph, DirectedVertex, TreeMultiset} = dataStructureTyped; ``` ![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/examples/dfs-pre-order.webp?raw=true) ![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/examples/test-avl-tree.webp?raw=true) ![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/examples/map-graph.webp?raw=true) ![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/examples/test-graphs.webp?raw=true) ![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/examples/cut-off-trees-for-golf.webp?raw=true) ![](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/examples/parenthesis-check.webp?raw=true) ## API docs & Examples [API Docs](https://data-structure-typed-docs.vercel.app) [Live Examples](https://vivid-algorithm.vercel.app) [//]: # (Live Examples) Examples Repository ### Binary Search Tree (BST) snippet #### TS ```typescript import {BST, BSTNode} from 'data-structure-typed'; const bst = new BST(); bst.add(11); bst.add(3); bst.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]); bst.size === 16; // true bst.has(6); // true const node6 = bst.get(6); bst.getHeight(6) === 2; // true bst.getHeight() === 5; // true bst.getDepth(6) === 3; // true const leftMost = bst.getLeftMost(); leftMost?.id === 1; // true expect(leftMost?.id).toBe(1); bst.remove(6); bst.get(6); // null bst.isAVLBalanced(); // true or false const bfsIDs = bst.BFS(); bfsIDs[0] === 11; // true expect(bfsIDs[0]).toBe(11); const objBST = new BST>(); objBST.add(11, {id: 11, keyA: 11}); objBST.add(3, {id: 3, keyA: 3}); objBST.addMany([{id: 15, keyA: 15}, {id: 1, keyA: 1}, {id: 8, keyA: 8}, {id: 13, keyA: 13}, {id: 16, keyA: 16}, {id: 2, keyA: 2}, {id: 6, keyA: 6}, {id: 9, keyA: 9}, {id: 12, keyA: 12}, {id: 14, keyA: 14}, {id: 4, keyA: 4}, {id: 7, keyA: 7}, {id: 10, keyA: 10}, {id: 5, keyA: 5}]); objBST.remove(11); const avlTree = new AVLTree(); avlTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]) avlTree.isAVLBalanced(); // true avlTree.remove(10); avlTree.isAVLBalanced(); // true ``` #### JS ```javascript const {BST, BSTNode} = require('data-structure-typed'); const bst = new BST(); bst.add(11); bst.add(3); bst.addMany([15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]); bst.size === 16; // true bst.has(6); // true const node6 = bst.get(6); bst.getHeight(6) === 2; // true bst.getHeight() === 5; // true bst.getDepth(6) === 3; // true const leftMost = bst.getLeftMost(); leftMost?.id === 1; // true expect(leftMost?.id).toBe(1); bst.remove(6); bst.get(6); // null bst.isAVLBalanced(); // true or false const bfsIDs = bst.BFS(); bfsIDs[0] === 11; // true expect(bfsIDs[0]).toBe(11); const objBST = new BST(); objBST.add(11, {id: 11, keyA: 11}); objBST.add(3, {id: 3, keyA: 3}); objBST.addMany([{id: 15, keyA: 15}, {id: 1, keyA: 1}, {id: 8, keyA: 8}, {id: 13, keyA: 13}, {id: 16, keyA: 16}, {id: 2, keyA: 2}, {id: 6, keyA: 6}, {id: 9, keyA: 9}, {id: 12, keyA: 12}, {id: 14, keyA: 14}, {id: 4, keyA: 4}, {id: 7, keyA: 7}, {id: 10, keyA: 10}, {id: 5, keyA: 5}]); objBST.remove(11); const avlTree = new AVLTree(); avlTree.addMany([11, 3, 15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5]) avlTree.isAVLBalanced(); // true avlTree.remove(10); avlTree.isAVLBalanced(); // true ``` ### Directed Graph simple snippet #### TS or JS ```typescript import {DirectedGraph} from 'data-structure-typed'; const graph = new DirectedGraph(); graph.addVertex('A'); graph.addVertex('B'); graph.hasVertex('A'); // true graph.hasVertex('B'); // true graph.hasVertex('C'); // false graph.addEdge('A', 'B'); graph.hasEdge('A', 'B'); // true graph.hasEdge('B', 'A'); // false graph.removeEdgeSrcToDest('A', 'B'); graph.hasEdge('A', 'B'); // false graph.addVertex('C'); graph.addEdge('A', 'B'); graph.addEdge('B', 'C'); const topologicalOrderIds = graph.topologicalSort(); // ['A', 'B', 'C'] ``` ### Undirected Graph snippet #### TS or JS ```typescript import {UndirectedGraph} from 'data-structure-typed'; const graph = new UndirectedGraph(); graph.addVertex('A'); graph.addVertex('B'); graph.addVertex('C'); graph.addVertex('D'); graph.removeVertex('C'); graph.addEdge('A', 'B'); graph.addEdge('B', 'D'); const dijkstraResult = graph.dijkstra('A'); Array.from(dijkstraResult?.seen ?? []).map(vertex => vertex.id) // ['A', 'B', 'D'] ``` ## Data Structures [//]: # () [//]: # () [//]: # () [//]: # () [//]: # () [//]: # () [//]: # ()

Data Structure	Unit Test	Performance Test	API Documentation	Implemented
Binary Tree			Binary Tree
Binary Search Tree (BST)			BST
AVL Tree			AVLTree
Tree Multiset			TreeMultiset
Segment Tree			SegmentTree
Binary Indexed Tree			BinaryIndexedTree
Graph			AbstractGraph
Directed Graph			DirectedGraph
Undirected Graph			UndirectedGraph
Linked List			SinglyLinkedList
Singly Linked List			SinglyLinkedList
Doubly Linked List			DoublyLinkedList
Queue			Queue
Object Deque			ObjectDeque
Array Deque			ArrayDeque
Stack			Stack
Hash			HashTable
Coordinate Set			CoordinateSet
Coordinate Map			CoordinateMap
Heap			Heap
Priority Queue			PriorityQueue
Max Priority Queue			MaxPriorityQueue
Min Priority Queue			MinPriorityQueue
Trie			Trie

## API docs

# Why ## Complexities ### performance of Big O

Big O Notation	Type	Computations for 10 elements	Computations for 100 elements	Computations for 1000 elements
O(1)	Constant	1	1	1
O(log N)	Logarithmic	3	6	9
O(N)	Linear	10	100	1000
O(N log N)	n log(n)	30	600	9000
O(N^2)	Quadratic	100	10000	1000000
O(2^N)	Exponential	1024	1.26e+29	1.07e+301
O(N!)	Factorial	3628800	9.3e+157	4.02e+2567

### Data Structure Complexity

Data Structure	Access	Search	Insertion	Deletion	Comments
Array	1	n	n	n
Stack	n	n	1	1
Queue	n	n	1	1
Linked List	n	n	1	n
Hash Table	-	n	n	n	In case of perfect hash function costs would be O(1)
Binary Search Tree	n	n	n	n	In case of balanced tree costs would be O(log(n))
B-Tree	log(n)	log(n)	log(n)	log(n)
Red-Black Tree	log(n)	log(n)	log(n)	log(n)
AVL Tree	log(n)	log(n)	log(n)	log(n)
Bloom Filter	-	1	1	-	False positives are possible while searching

### Sorting Complexity

Name	Best	Average	Worst	Memory	Stable	Comments
Bubble sort	n	n²	n²	1	Yes
Insertion sort	n	n²	n²	1	Yes
Selection sort	n²	n²	n²	1	No
Heap sort	n log(n)	n log(n)	n log(n)	1	No
Merge sort	n log(n)	n log(n)	n log(n)	n	Yes
Quick sort	n log(n)	n log(n)	n²	log(n)	No	Quicksort is usually done in-place with O(log(n)) stack space
Shell sort	n log(n)	depends on gap sequence	n (log(n))²	1	No
Counting sort	n + r	n + r	n + r	n + r	Yes	r - biggest number in array
Radix sort	n * k	n * k	n * k	n + k	Yes	k - length of longest key

[//]: # (![overview diagram](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/assets/overview-diagram-of-data-structures.png?raw=true)) ![complexities](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/assets/complexities-diff.jpg?raw=true) ![complexities of data structures](https://github.com/zrwusa/assets/blob/master/images/data-structure-typed/assets/data-structure-complexities.jpg?raw=true)