What

Brief

This is a standalone Linked List 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 linked-list-typed --save

yarn

yarn add linked-list-typed

snippet

basic DoublyLinkedList creation and push operation

 // Create a simple DoublyLinkedList with initial values
    const list = new DoublyLinkedList([1, 2, 3, 4, 5]);

    // Verify the list maintains insertion order
    console.log([...list]); // [1, 2, 3, 4, 5];

    // Check length
    console.log(list.length); // 5;

    // Push a new element to the end
    list.push(6);
    console.log(list.length); // 6;
    console.log([...list]); // [1, 2, 3, 4, 5, 6];

DoublyLinkedList pop and shift operations

 const list = new DoublyLinkedList<number>([10, 20, 30, 40, 50]);

    // Pop removes from the end
    const last = list.pop();
    console.log(last); // 50;

    // Shift removes from the beginning
    const first = list.shift();
    console.log(first); // 10;

    // Verify remaining elements
    console.log([...list]); // [20, 30, 40];
    console.log(list.length); // 3;

DoublyLinkedList for...of iteration and map operation

 const list = new DoublyLinkedList<number>([1, 2, 3, 4, 5]);

    // Iterate through list
    const doubled = list.map(value => value * 2);
    console.log(doubled.length); // 5;

    // Use for...of loop
    const result: number[] = [];
    for (const item of list) {
      result.push(item);
    }
    console.log(result); // [1, 2, 3, 4, 5];

Browser history

 const browserHistory = new DoublyLinkedList<string>();

    browserHistory.push('home page');
    browserHistory.push('search page');
    browserHistory.push('details page');

    console.log(browserHistory.last); // 'details page';
    console.log(browserHistory.pop()); // 'details page';
    console.log(browserHistory.last); // 'search page';

DoublyLinkedList for LRU cache implementation

 interface CacheEntry {
      key: string;
      value: string;
    }

    // Simulate LRU cache using DoublyLinkedList
    // DoublyLinkedList is perfect because:
    // - O(1) delete from any position
    // - O(1) push to end
    // - Bidirectional traversal for LRU policy

    const cacheList = new DoublyLinkedList<CacheEntry>();
    const maxSize = 3;

    // Add cache entries
    cacheList.push({ key: 'user:1', value: 'Alice' });
    cacheList.push({ key: 'user:2', value: 'Bob' });
    cacheList.push({ key: 'user:3', value: 'Charlie' });

    // Try to add a new entry when cache is full
    if (cacheList.length >= maxSize) {
      // Remove the oldest (first) entry
      const evicted = cacheList.shift();
      console.log(evicted?.key); // 'user:1';
    }

    // Add new entry
    cacheList.push({ key: 'user:4', value: 'Diana' });

    // Verify current cache state
    console.log(cacheList.length); // 3;
    const cachedKeys = [...cacheList].map(entry => entry.key);
    console.log(cachedKeys); // ['user:2', 'user:3', 'user:4'];

    // Access entry (in real LRU, this would move it to end)
    const foundEntry = [...cacheList].find(entry => entry.key === 'user:2');
    console.log(foundEntry?.value); // 'Bob';

API docs & Examples

API Docs

Live Examples

Examples Repository

Data Structures

Standard library data structure comparison

Benchmark

Built-in classic algorithms

Software Engineering Design Standards