Tree: What is a Tree Structure? Easily Understand with Real-Life Examples
This article uses a life analogy to explain the "tree" in data structures. The core is that a tree is similar to a tree in life: it has a root node (starting point), child/parent nodes (branches and their source), leaf nodes (no descendants), and subtrees (nodes and their descendants), with the characteristics of being non-linear, branching, and hierarchical. Unlike linear linked lists (single path), trees can have multiple branches (e.g., the root node can have multiple child nodes). Tree structures are ubiquitous in life: family relationships take elders as the root, corporate structures take the CEO as the root, and computer file systems take the disk as the root, all reflecting hierarchical branches. The core advantage of trees is their efficient handling of hierarchical branching problems, such as database indexing, navigation path planning, and game scene construction. Understanding tree structures allows one to master the thinking of handling branching problems. In life, families, companies, and file systems are typical applications of trees.
Read MoreHow to Learn Tree Traversal? Easily Understand Preorder, Inorder, and Postorder Traversals
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 their core difference lying in the timing of visiting the root node. - **Preorder Traversal (Root → Left → Right)**: Visit the root first, then recursively traverse the left subtree, and finally the right subtree. Example: 1→2→4→5→3→6→7. - **Inorder Traversal (Left → Root → Right)**: Recursively traverse the left subtree first, then visit the root, and finally the right subtree. Example: 4→2→5→1→6→3→7. - **Postorder Traversal (Left → Right → Root)**: Recursively traverse the left subtree first, then the right subtree, and finally visit the root. Example: 4→5→2→6→7→3→1. Memory mnemonic: Preorder has the root first, inorder has the root in the middle, postorder has the root last. In applications, preorder is used for tree copying, inorder sorts binary search trees, and postorder is used for node deletion. Traversal essentially embodies the recursive thought; mastering the order and scenarios enables proficiency.
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