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Introduce

This repository is mainly used to record my leetcode exercises, algorithm templates, and other related exercises.

You can submit a PR and share your better code with us (please use JavaScript/TypeScript)

Format

When submitting code, you need to use the unified prettier rules for code formatting. For code formatting in batches, you can execute npx prettier --write .

Catalogue Introduction

It is planned to update the repository to use a TS project. Different directories represent different content, for example:

Catalogue	Abstract
record	Leetcode topic collection
structure	TypeScript related data custom structure
experiment	Experiments with common problems
utils	Some commonly used tools

In addition, the project is connected to the jest code unit test. For jest-related content, you can view it in detail jestjs.io。

Leetcode

As a front-end developer, algorithmic ability is also necessary in order to use relevant knowledge to optimize problems. Leetcode is the easiest way for beginners to learn algorithms, and I plan to record related problem-solving code in the record folder. view details.

Data Structure

In TypeScript, there are no built-in implementations of common data structures such as queues and stacks. Therefore, we have provided some utility classes for data structures in the structure directory, which make it easy for me to use them when solving problems.

Stack

Two methods have been used to implement the Stack data structure. One method is through arrays, and the other is through hash tables. The purpose is to be able to determine whether an element exists in the stack in O(1) time complexity.

view the code

Method Name	Function
push(element)	Insert a new node into the stack
pop()	Get the top node on the stack and pop
peek()	Get the top node on the stack
isEmpty()	Determine if the stack is empty
size()	The number of data in the stack
clear()	Clear the stack

BST

view the code

Method Name	Function
insert(key)	Insert a new node into the tree
search(key)	Find a node in the tree
remove(key)	Remove a node from the tree
min()	Return the minimum value of a node in the tree
max()	Return the maximum node in the tree
preOrderTraverse()	Traverse all nodes in pre-order
inOrderTraverse()	Traverse all nodes in in-order
postOrderTraverse()	Traverse all nodes in post-order

Additional methods:

preOrderTraverseNode(
    node: TreeNode<T> | null = this.root,
    callback?: (value: T) => {},
): void {
    if (node !== null) {
        if (callback === undefined) {
            console.log(node.val);
        } else {
            callback(node.val);
        }
        this.preOrderTraverseNode(node.left, callback);
        this.preOrderTraverseNode(node.right, callback);
    }
}

As you can tell from the code, preOrderTraverseNode is passed in as a callback function for the purpose of being able to process a node's information directly.

const bst = new BST();
bst.insert(5);
bst.insert(3);
bst.insert(4);
bst.insert(2);
bst.preOrderTraverseNode(bst.root, (v: number) => {});

AVL

AVL inherits from BST and prevents BST from going too extreme and degenerating binary trees into chained tables, where the time complexity of the lookup becomes O(N). More can be found at OI WIKI

view the code

const avl = new AVL();
avl.insert(5);
avl.insert(6);
avl.insert(4);
avl.insert(8);
avl.insert(7);
avl.insert(10);
avl.insert(9);
avl.insert(11);
avl.inOrderTraverseNode();