队列：队列的“先进先出”如何实现？简单例子说明
队列是遵循“先进先出”（FIFO）原则的数据结构，仅能在队尾入队、队头出队，核心概念包括队头（最早元素）、队尾（最晚元素），基本操作为入队（Enqueue）和出队（Dequeue）。 以数组实现为例，需front（队头指针）、rear（队尾指针）及固定容量数组。队空条件为front == rear，队满为rear == max_size；入队时rear后移存储元素，出队时front后移取出元素。 实例演示：容量5的队列，初始front=0、rear=0；入队1、2、3后rear=3，队列[1,2,3]；出队1（front=1），再入队4（rear=4）；入队5后队列满，出队2（front=2），最终队列[3,4,5]。 应用场景包括任务调度、广度优先搜索（BFS）、打印机队列、网络请求等，在数据处理和任务排队中作用关键。
Read MoreThe Art of Queuing: Applications of Queues in Data Structures
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 queue is a data structure that follows the "First-In-First-Out" (FIFO) principle. Its core operations include enqueue (adding an element to the tail of the queue) and dequeue (removing the earliest added element from the front of the queue). Additionally, operations like viewing the front element and checking if the queue is empty are also supported. Queues differ from stacks (which follow the "Last-In-First-Out" (LIFO) principle); the former adheres to "first-come, first-served," while the latter reflects "last-come, first-served." Queues have wide applications: In computer task scheduling, systems process multiple tasks in a queue (e.g., programs opened earlier receive CPU time first); the BFS (Breadth-First Search) algorithm uses a queue to expand nodes level by level, enabling shortest path searches in mazes; during e-commerce promotions, queues buffer user requests to prevent system overload; in multi-threading, producers add data to a queue, and consumers process it in order, facilitating asynchronous collaboration. Learning queues helps solve problems such as processing data in sequence and avoiding resource conflicts, making it a fundamental tool in programming and algorithms. Understanding the "First-In-First-Out" principle contributes to efficiently solving practical problems.
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