Package detail

binary-tree-typed

zrwusa664MIT2.0.3

Binary Tree. Javascript & Typescript Data Structure.

binary tree, binary tree data structure, binary tree, binarytree

readme

NPM GitHub top language npm eslint npm bundle size npm bundle size npm

What

Brief

This is a standalone Binary 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 binary-tree-typed --save

yarn

yarn add binary-tree-typed

snippet

determine loan approval using a decision tree

    // Decision tree structure
    const loanDecisionTree = new BinaryTree<string>(
      ['stableIncome', 'goodCredit', 'Rejected', 'Approved', 'Rejected'],
      { isDuplicate: true }
    );

    function determineLoanApproval(
      node?: BinaryTreeNode<string> | null,
      conditions?: { [key: string]: boolean }
    ): string {
      if (!node) throw new Error('Invalid node');

      // If it's a leaf node, return the decision result
      if (!node.left && !node.right) return node.key;

      // Check if a valid condition exists for the current node's key
      return conditions?.[node.key]
        ? determineLoanApproval(node.left, conditions)
        : determineLoanApproval(node.right, conditions);
    }

    // Test case 1: Stable income and good credit score
    console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: true, goodCredit: true })); // 'Approved'

    // Test case 2: Stable income but poor credit score
    console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: true, goodCredit: false })); // 'Rejected'

    // Test case 3: No stable income
    console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: false, goodCredit: true })); // 'Rejected'

    // Test case 4: No stable income and poor credit score
    console.log(determineLoanApproval(loanDecisionTree.root, { stableIncome: false, goodCredit: false })); // 'Rejected'

evaluate the arithmetic expression represented by the binary tree

    const expressionTree = new BinaryTree<number | string>(['+', 3, '*', null, null, 5, '-', null, null, 2, 8]);

    function evaluate(node?: BinaryTreeNode<number | string> | null): number {
      if (!node) return 0;

      if (typeof node.key === 'number') return node.key;

      const leftValue = evaluate(node.left); // Evaluate the left subtree
      const rightValue = evaluate(node.right); // Evaluate the right subtree

      // Perform the operation based on the current node's operator
      switch (node.key) {
        case '+':
          return leftValue + rightValue;
        case '-':
          return leftValue - rightValue;
        case '*':
          return leftValue * rightValue;
        case '/':
          return rightValue !== 0 ? leftValue / rightValue : 0; // Handle division by zero
        default:
          throw new Error(`Unsupported operator: ${node.key}`);
      }
    }

    console.log(evaluate(expressionTree.root)); // -27

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Data Structure Unit Test Performance Test API Docs
Binary Tree Binary Tree

Standard library data structure comparison

Data Structure Typed C++ STL java.util Python collections
BinaryTree<K, V> - - -

Benchmark

binary-tree
test nametime taken (ms)executions per secsample deviation
1,000 add randomly12.3580.997.17e-5
1,000 add & delete randomly15.9862.587.98e-4
1,000 addMany10.9691.270.00
1,000 get18.6153.730.00
1,000 dfs164.206.090.04
1,000 bfs58.8417.000.01
1,000 morris256.663.907.70e-4

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.