What
Brief
This is a standalone BST (Binary Search Tree) data structure from the data-structure-typed collection. If you wish to
access more data structures or advanced features, you can transition to directly installing the
complete data-structure-typed package
How
install
npm
npm i bst-typed --save
yarn
yarn add bst-typed
methods
snippet
TS
import {BST, BSTNode} from 'data-structure-typed';
const bst = new BST();
bst instanceof BST;
bst.add(11);
bst.add(3);
const idsAndValues = [15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];
bst.addMany(idsAndValues);
bst.root instanceof BSTNode;
if (bst.root) bst.root.id;
bst.size;
bst.has(6);
const node6 = bst.get(6);
node6 && bst.getHeight(6);
node6 && bst.getDepth(6);
const nodeId10 = bst.get(10);
nodeId10?.id;
const nodeVal9 = bst.get(9, 'val');
nodeVal9?.id;
const leftMost = bst.getLeftMost();
leftMost?.id;
const node15 = bst.get(15);
const minNodeBySpecificNode = node15 && bst.getLeftMost(node15);
minNodeBySpecificNode?.id;
const subTreeSum = node15 && bst.subTreeSum(15);
subTreeSum;
const lesserSum = bst.lesserSum(10);
lesserSum;
node15 instanceof BSTNode;
const node11 = bst.get(11);
node11 instanceof BSTNode;
const dfsInorderNodes = bst.DFS('in', 'node');
dfsInorderNodes[0].id;
dfsInorderNodes[dfsInorderNodes.length - 1].id;
bst.perfectlyBalance();
bst.isPerfectlyBalanced();
const bfsNodesAfterBalanced = bst.BFS('node');
bfsNodesAfterBalanced[0].id;
bfsNodesAfterBalanced[bfsNodesAfterBalanced.length - 1].id;
const removed11 = bst.remove(11, true);
removed11 instanceof Array;
if (removed11[0].deleted) removed11[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight(15);
const removed1 = bst.remove(1, true);
removed1 instanceof Array;
if (removed1[0].deleted) removed1[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed4 = bst.remove(4, true);
removed4 instanceof Array;
if (removed4[0].deleted) removed4[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed10 = bst.remove(10, true);
if (removed10[0].deleted) removed10[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed15 = bst.remove(15, true);
if (removed15[0].deleted) removed15[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed5 = bst.remove(5, true);
if (removed5[0].deleted) removed5[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed13 = bst.remove(13, true);
if (removed13[0].deleted) removed13[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed3 = bst.remove(3, true);
if (removed3[0].deleted) removed3[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed8 = bst.remove(8, true);
if (removed8[0].deleted) removed8[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed6 = bst.remove(6, true);
if (removed6[0].deleted) removed6[0].deleted.id;
bst.remove(6, true).length;
bst.isAVLBalanced();
bst.getHeight();
const removed7 = bst.remove(7, true);
if (removed7[0].deleted) removed7[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed9 = bst.remove(9, true);
if (removed9[0].deleted) removed9[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed14 = bst.remove(14, true);
if (removed14[0].deleted) removed14[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
bst.isAVLBalanced();
const bfsIDs = bst.BFS();
bfsIDs[0];
bfsIDs[1];
bfsIDs[2];
const bfsNodes = bst.BFS('node');
bfsNodes[0].id;
bfsNodes[1].id;
bfsNodes[2].id;
JS
const {BST, BSTNode} = require('data-structure-typed');
const bst = new BST();
bst instanceof BST;
bst.add(11);
bst.add(3);
const idsAndValues = [15, 1, 8, 13, 16, 2, 6, 9, 12, 14, 4, 7, 10, 5];
bst.addMany(idsAndValues);
bst.root instanceof BSTNode;
if (bst.root) bst.root.id;
bst.size;
bst.has(6);
const node6 = bst.get(6);
node6 && bst.getHeight(6);
node6 && bst.getDepth(6);
const nodeId10 = bst.get(10);
nodeId10?.id;
const nodeVal9 = bst.get(9, 'val');
nodeVal9?.id;
const leftMost = bst.getLeftMost();
leftMost?.id;
const node15 = bst.get(15);
const minNodeBySpecificNode = node15 && bst.getLeftMost(node15);
minNodeBySpecificNode?.id;
const subTreeSum = node15 && bst.subTreeSum(15);
subTreeSum;
const lesserSum = bst.lesserSum(10);
lesserSum;
node15 instanceof BSTNode;
const node11 = bst.get(11);
node11 instanceof BSTNode;
const dfsInorderNodes = bst.DFS('in', 'node');
dfsInorderNodes[0].id;
dfsInorderNodes[dfsInorderNodes.length - 1].id;
bst.perfectlyBalance();
bst.isPerfectlyBalanced();
const bfsNodesAfterBalanced = bst.BFS('node');
bfsNodesAfterBalanced[0].id;
bfsNodesAfterBalanced[bfsNodesAfterBalanced.length - 1].id;
const removed11 = bst.remove(11, true);
removed11 instanceof Array;
if (removed11[0].deleted) removed11[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight(15);
const removed1 = bst.remove(1, true);
removed1 instanceof Array;
if (removed1[0].deleted) removed1[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed4 = bst.remove(4, true);
removed4 instanceof Array;
if (removed4[0].deleted) removed4[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed10 = bst.remove(10, true);
if (removed10[0].deleted) removed10[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed15 = bst.remove(15, true);
if (removed15[0].deleted) removed15[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed5 = bst.remove(5, true);
if (removed5[0].deleted) removed5[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed13 = bst.remove(13, true);
if (removed13[0].deleted) removed13[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed3 = bst.remove(3, true);
if (removed3[0].deleted) removed3[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed8 = bst.remove(8, true);
if (removed8[0].deleted) removed8[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed6 = bst.remove(6, true);
if (removed6[0].deleted) removed6[0].deleted.id;
bst.remove(6, true).length;
bst.isAVLBalanced();
bst.getHeight();
const removed7 = bst.remove(7, true);
if (removed7[0].deleted) removed7[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed9 = bst.remove(9, true);
if (removed9[0].deleted) removed9[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
const removed14 = bst.remove(14, true);
if (removed14[0].deleted) removed14[0].deleted.id;
bst.isAVLBalanced();
bst.getHeight();
bst.isAVLBalanced();
const bfsIDs = bst.BFS();
bfsIDs[0];
bfsIDs[1];
bfsIDs[2];
const bfsNodes = bst.BFS('node');
bfsNodes[0].id;
bfsNodes[1].id;
bfsNodes[2].id;
API docs & Examples
API Docs
Live Examples
Examples Repository
Data Structures
Data Structure | Unit Test | Performance Test | API Docs |
---|
Binary Search Tree (BST) | | | BST |
Standard library data structure comparison
Data Structure Typed | C++ STL | java.util | Python collections |
---|
BST<K, V> | - | - | - |
Benchmark
bst
test name | time taken (ms) | executions per sec | sample deviation |
---|
10,000 add randomly | 31.59 | 31.66 | 2.74e-4 |
10,000 add & delete randomly | 74.56 | 13.41 | 8.32e-4 |
10,000 addMany | 29.16 | 34.30 | 0.00 |
10,000 get | 29.24 | 34.21 | 0.00 |
Built-in classic algorithms
Algorithm | Function Description | Iteration Type |
---|
Binary Tree DFS | Traverse a binary tree in a depth-first manner, starting from the root node, first visiting the left subtree,
and then the right subtree, using recursion.
| Recursion + Iteration |
Binary Tree BFS | Traverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level
from left to right.
| Iteration |
Binary Tree Morris | Morris traversal is an in-order traversal algorithm for binary trees with O(1) space complexity. It allows tree
traversal without additional stack or recursion.
| Iteration |
Software Engineering Design Standards
Principle | Description |
---|
Practicality | Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names. |
Extensibility | Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures. |
Modularization | Includes data structure modularization and independent NPM packages. |
Efficiency | All methods provide time and space complexity, comparable to native JS performance. |
Maintainability | Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns. |
Testability | Automated and customized unit testing, performance testing, and integration testing. |
Portability | Plans for porting to Java, Python, and C++, currently achieved to 80%. |
Reusability | Fully decoupled, minimized side effects, and adheres to OOP. |
Security | Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects. |
Scalability | Data structure software does not involve load issues. |