Stack: What Does "Last-In-First-Out" Mean? Principle Diagram
This article uses "stacking plates" as an example to explain the core concepts of the data structure "stack". A stack is a linear list where insertions and deletions can only be performed from one end (the top), with the other end being the bottom. Its core feature is "Last-In-First-Out" (LIFO) — the last element added is the first to be removed. Basic operations of a stack include: push (adding an element to the top), pop (removing and returning the top element), top (viewing the top element), and empty (checking if the stack is empty). For example, when stacking plates, new plates are placed on top (push), and the top plate must be taken first (pop), which aligns with LIFO. Stacks are widely applied in life and programming: bracket matching (using the stack to record left brackets, popping to match right brackets), function call stacks (functions called later return first), and browser back functionality (successively popping recently visited webpages). Understanding the "LIFO" feature of stacks helps solve problems like recursion and dynamic programming, making it a foundational tool in data structures.
Read MoreStacks in Daily Life: Why Are Stacks the First Choice for Data Structure Beginners?
The article introduces "stack" through daily scenarios such as stacking plates and browser backtracking, with its core feature being "Last-In-First-Out" (LIFO). A stack is a container that can only be operated on from the top, with core operations being "Push" (pushing onto the stack) and "Pop" (popping from the stack). As a first choice for data structure introduction, the stack has a simple logic (only the LIFO rule), clear operations (only two basic operations), extensive applications (scenarios like bracket matching, browser backtracking, recursion, etc.), and can be easily implemented using arrays or linked lists. It serves as a foundation for learning subsequent structures like queues and trees, helps establish clear programming thinking, and is a "stepping stone" for understanding data structures.
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