Heap Data Structure Visualizer

STEM Interactive Visual Learning Program at TEC-Bridge AI

Heap Setup

Heap Operations

Heap Visualization

Operation Steps

How to Use

Choose Heap Type: Select Max Heap or Min Heap
Insert Values: Enter a number and click "Insert"
Random Heap: Click Random Heap to instantly generate a sample heap with random values.
Extract Root: Remove and return the root element
Peek Root: View the root element without removing it
Reset: Clear the heap

Heap Concept

Heap is a complete binary tree that satisfies the heap property. It's commonly used to implement priority queues.

Key Characteristics:

Complete binary tree structure
Heap property: parent-child relationship
Efficient insertion and extraction
Array-based implementation

Max Heap: Parent nodes are greater than or equal to their children. The largest element is at the root.

Min Heap: Parent nodes are less than or equal to their children. The smallest element is at the root.

Purpose & Applications

Priority queues
Heap sort algorithm
Graph algorithms (Dijkstra's, Prim's)
Task scheduling
Memory management

Time & Space Complexity

Operation	Time Complexity	Space Complexity
Insert	O(log n)	O(1)
Extract Root	O(log n)	O(1)
Peek Root	O(1)	O(1)
Build Heap	O(n)	O(1)

Strengths & Limitations

Strengths:

Efficient priority queue operations
Space-efficient array representation
Guaranteed logarithmic time complexity
Cache-friendly due to array structure

Limitations:

No efficient search for arbitrary elements
Not suitable for sorted traversal
Limited flexibility compared to other trees

Heap Code Implementation

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