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The article explains the necessity of time complexity: due to differences in hardware and compilers, direct timing is impractical, and an abstract description of the algorithm's efficiency trend is re

Hash tables map keys to array slots via hash functions, and hash collisions occur when different keys map to the same slot. The core solution is to find new positions for colliding elements, with the

Trees are fundamental data structures, and traversal is the process of visiting all nodes. This article focuses on explaining the preorder, inorder, and postorder traversals of binary trees, with thei

Recursion is a problem-solving method that "calls itself", breaking down large problems into smaller, similar subproblems until the subproblems can be solved directly, then returning results layer by

A heap is a special structure based on a complete binary tree, stored in an array, and satisfies the properties of a max heap (parent node value ≥ child node) or a min heap (parent node value ≤ child

This article introduces search algorithms in computers, focusing on linear search and binary search. Linear search (sequential search) is a basic method that checks data one by one from the beginning

Bubble Sort is a basic sorting algorithm that simulates the "bubble rising" process to gradually "bubble up" the largest element to the end of the array for sorting. The core idea is to repeatedly com

The article uses the analogy of searching for a book to introduce the problem: sequential search of data (such as arrays) is inefficient, while a hash table is an efficient storage tool. The core of a

A binary tree is a fundamental data structure where each node has at most two child nodes (left and right), and nodes with no descendants are called leaves. Core terms include: root node (the topmost

This article introduces the queue data structure. In daily life, queuing (such as getting meals in a cafeteria) embodies the "first-come, first-served" principle, which is the prototype of a queue. A