DSAVerseAlgorithm Visualizer

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Tree Algorithms

Master TreeStructures Visually

Explore tree traversals, BST operations, and balanced tree algorithms with interactive visualizations.

12+ Tree Algorithms

Real-time Visualization

Interactive Traversal

Interactive Visualizations

Choose Your AlgorithmStart Visualizing

Click on any algorithm card to see it in action with interactive step-by-step visualization

Binary Tree Traversal

Inorder, Preorder, and Postorder traversals to visit all nodes in specific order.

Worst Case:O(n)

BST Operations

Insert, delete, and search operations in Binary Search Tree.

Average:O(log n)

Worst Case:O(n)

AVL Tree

Self-balancing BST with rotations to maintain height balance.

Average:O(log n)

Worst Case:O(log n)

Red-Black Tree

Self-balancing BST with color properties for efficient operations.

Average:O(log n)

Worst Case:O(log n)

B-Tree

Self-balancing tree for databases with multiple keys per node.

Average:O(log n)

Worst Case:O(log n)

Segment Tree

Range query tree for efficient array segment operations.

Average:O(log n)

Worst Case:O(log n)

Fenwick Tree (BIT)

Binary Indexed Tree for efficient prefix sum calculations.

Average:O(log n)

Worst Case:O(log n)

Trie (Prefix Tree)

Tree for efficient string storage and prefix-based searches.

Worst Case:O(m)

Heap (Binary Heap)

Complete binary tree for priority queue implementation.

Average:O(log n)

Worst Case:O(log n)

Suffix Tree

Tree containing all suffixes of a string for pattern matching.

Worst Case:O(n)

Splay Tree

Self-adjusting BST that moves accessed elements to root.

Average:O(log n)

Worst Case:O(n)

Treap

Randomized BST combining binary tree and heap properties.

Average:O(log n)

Worst Case:O(log n)

Each algorithm includes interactive visualization, code implementation, and complexity analysis

Complete Collection

All Tree AlgorithmsDetailed Overview

Explore 12 tree algorithms with complexity analysis, pros & cons, and use cases

12

Total Algorithms

4

Self-Balancing

6

O(log n) Guaranteed

3

Specialized Trees

Complete AlgorithmComparison Table

Compare all 12 tree structures at a glance

Tree Structure	Type	Search	Insert	Delete	Space	Balanced
Binary Tree Traversal	Traversal	`O(n)`	`N/A`	`N/A`	`O(h)`
BST	Binary Search	`O(log n)*`	`O(log n)*`	`O(log n)*`	`O(n)`
AVL Tree	Self-Balancing	`O(log n)`	`O(log n)`	`O(log n)`	`O(n)`
Red-Black Tree	Self-Balancing	`O(log n)`	`O(log n)`	`O(log n)`	`O(n)`
B-Tree	Multi-way	`O(log n)`	`O(log n)`	`O(log n)`	`O(n)`
Segment Tree	Range Query	`O(log n)`	`O(n)`	`N/A`	`O(n)`
Fenwick Tree	Range Query	`O(log n)`	`O(log n)`	`O(log n)`	`O(n)`
Trie	String	`O(m)`	`O(m)`	`O(m)`	`O(alphabet×n×m)`
Heap	Priority Queue	`O(n)`	`O(log n)`	`O(log n)`	`O(n)`
Suffix Tree	String	`O(m)`	`O(n)`	`N/A`	`O(n)`
Splay Tree	Self-Adjusting	`O(log n)*`	`O(log n)*`	`O(log n)*`	`O(n)`
Treap	Randomized	`O(log n)*`	`O(log n)*`	`O(log n)*`	`O(n)`

Legend & Notes

n: Number of elements/nodes

h: Height of tree

m: Length of string/key

*: Amortized or average case

Balanced: Self-balancing property

N/A: Operation not applicable

Space: Auxiliary space complexity

BST worst: Can degrade to O(n)

Trie space: Depends on alphabet size