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Red-Black Tree Data Structure Visualizer

STEM Interactive Visual Learning Program at TEC-Bridge AI

Red-Black Tree Setup

Red-Black Tree Operations

Tree Visualization

(Red-Black Tree maintains balance through color rules and rotations)

Operation Steps

How to Use

  1. Insert: Enter a value and click "Insert"
  2. Delete: Enter a value and click "Delete"
  3. Search: Enter a value and click "Search"
  4. Random RBT: Click to generate a random tree
  5. Reset: Click to clear the tree

Red-Black Tree Concept

Red-Black Tree (RBT) is a self-balancing binary search tree where each node has a color (red or black).

Key Properties:

  • Every node is red or black
  • Root is always black
  • Red nodes have black children
  • All paths have same black-height
  • Guarantees O(log n) operations

RBT maintains balance through color rules and rotations, ensuring efficient search, insert, and delete operations.

Purpose & Applications

  • Database indexing
  • File systems
  • Java TreeMap and TreeSet
  • C++ std::map and std::set
  • Linux kernel scheduling

Strengths & Limitations

Strengths:

  • Self-balancing automatically
  • Guaranteed O(log n) operations
  • Fewer rotations than AVL

Limitations:

  • More complex implementation
  • Not as tight as AVL trees

Time & Space Complexity

Operation Average Case Worst Case
Insert O(log n) O(log n)
Delete O(log n) O(log n)
Search O(log n) O(log n)
Space O(n) O(n)

Red-Black Tree Code Implementation

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