![NPM](https://img.shields.io/npm/l/binary-tree-typed)
![GitHub top language](https://img.shields.io/github/languages/top/zrwusa/data-structure-typed)
![npm](https://img.shields.io/npm/dw/binary-tree-typed)
![eslint](https://aleen42.github.io/badges/src/eslint.svg)
![npm bundle size](https://img.shields.io/bundlephobia/minzip/binary-tree-typed)
![npm bundle size](https://img.shields.io/bundlephobia/min/binary-tree-typed)
![npm](https://img.shields.io/npm/v/binary-tree-typed)

# 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](https://www.npmjs.com/package/data-structure-typed) package

# How

## install

### npm

```bash
npm i binary-tree-typed --save
```

### yarn

```bash
yarn add binary-tree-typed
```

### snippet

[//]: # (No deletion!!! Start of Example Replace Section)

### determine loan approval using a decision tree
```typescript
    // 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
```typescript
    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
```

[//]: # (No deletion!!! End of Example Replace Section)


## API docs & Examples

[API Docs](https://data-structure-typed-docs.vercel.app)

[Live Examples](https://vivid-algorithm.vercel.app)

<a href="https://github.com/zrwusa/vivid-algorithm" target="_blank">Examples Repository</a>

## Data Structures

<table>
<thead>
<tr>
<th>Data Structure</th>
<th>Unit Test</th>
<th>Performance Test</th>
<th>API Docs</th>
</tr>
</thead>
<tbody>
<tr>
<td>Binary Tree</td>
<td><img src="https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg" alt=""></td>
<td><img src="https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg" alt=""></td>
<td><a href="https://data-structure-typed-docs.vercel.app/classes/BinaryTree.html"><span>Binary Tree</span></a></td>
</tr>
</tbody>
</table>

## Standard library data structure comparison

<table>
  <thead>
  <tr>
    <th>Data Structure Typed</th>
    <th>C++ STL</th>
    <th>java.util</th>
    <th>Python collections</th>
  </tr>
  </thead>
  <tbody>

  <tr>
    <td>BinaryTree&lt;K, V&gt;</td>
    <td>-</td>
    <td>-</td>
    <td>-</td>
  </tr>

  </tbody>
</table>

## Benchmark

[//]: # (No deletion!!! Start of Replace Section)
<div class="json-to-html-collapse clearfix 0">
      <div class='collapsible level0' ><span class='json-to-html-label'>binary-tree</span></div>
      <div class="content"><table style="display: table; width:100%; table-layout: fixed;"><tr><th>test name</th><th>time taken (ms)</th><th>executions per sec</th><th>sample deviation</th></tr><tr><td>1,000 add randomly</td><td>12.35</td><td>80.99</td><td>7.17e-5</td></tr><tr><td>1,000 add & delete randomly</td><td>15.98</td><td>62.58</td><td>7.98e-4</td></tr><tr><td>1,000 addMany</td><td>10.96</td><td>91.27</td><td>0.00</td></tr><tr><td>1,000 get</td><td>18.61</td><td>53.73</td><td>0.00</td></tr><tr><td>1,000 dfs</td><td>164.20</td><td>6.09</td><td>0.04</td></tr><tr><td>1,000 bfs</td><td>58.84</td><td>17.00</td><td>0.01</td></tr><tr><td>1,000 morris</td><td>256.66</td><td>3.90</td><td>7.70e-4</td></tr></table></div>
    </div>

[//]: # (No deletion!!! End of Replace Section)

## Built-in classic algorithms

<table>
  <thead>
  <tr>
    <th>Algorithm</th>
    <th>Function Description</th>
    <th>Iteration Type</th>
  </tr>
  </thead>
  <tbody>
  <tr>
    <td>Binary Tree DFS</td>
    <td>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.
    </td>
    <td>Recursion + Iteration</td>
  </tr>
  <tr>
    <td>Binary Tree BFS</td>
    <td>Traverse a binary tree in a breadth-first manner, starting from the root node, visiting nodes level by level
      from left to right.
    </td>
    <td>Iteration</td>
  </tr>
  <tr>
    <td>Binary Tree Morris</td>
    <td>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.
    </td>
    <td>Iteration</td>
  </tr>
  </tbody>
</table>

## Software Engineering Design Standards
<table>
    <tr>
        <th>Principle</th>
        <th>Description</th>
    </tr>
    <tr>
        <td>Practicality</td>
        <td>Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.</td>
    </tr>
    <tr>
        <td>Extensibility</td>
        <td>Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.</td>
    </tr>
    <tr>
        <td>Modularization</td>
        <td>Includes data structure modularization and independent NPM packages.</td>
    </tr>
    <tr>
        <td>Efficiency</td>
        <td>All methods provide time and space complexity, comparable to native JS performance.</td>
    </tr>
    <tr>
        <td>Maintainability</td>
        <td>Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.</td>
    </tr>
    <tr>
        <td>Testability</td>
        <td>Automated and customized unit testing, performance testing, and integration testing.</td>
    </tr>
    <tr>
        <td>Portability</td>
        <td>Plans for porting to Java, Python, and C++, currently achieved to 80%.</td>
    </tr>
    <tr>
        <td>Reusability</td>
        <td>Fully decoupled, minimized side effects, and adheres to OOP.</td>
    </tr>
    <tr>
        <td>Security</td>
        <td>Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.</td>
    </tr>
    <tr>
        <td>Scalability</td>
        <td>Data structure software does not involve load issues.</td>
    </tr>
</table>