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Prefix Tree (Trie) Data Structure Visualizer

STEM Interactive Visual Learning Program at TEC-Bridge AI

Trie Setup

Trie Operations

Trie Visualization

Operation Steps

How to Use

  1. Insert Word: Enter a word and click "Insert Word"
  2. Sample Words: Click Sample Words to generate example trie.
  3. Search Word: Find complete words in the trie
  4. Search Prefix: Find words with given prefix
  5. Reset: Clear the entire trie

Prefix Tree (Trie) Concept

Prefix Tree (Trie) is a tree data structure used for storing and searching strings efficiently by sharing common prefixes.

Key Characteristics:

  • Each node represents a character
  • Root represents empty string
  • Paths from root to nodes form prefixes
  • End-of-word markers identify complete words

Applications: Autocomplete, spell checkers, IP routing, and string matching algorithms.

Purpose & Applications

  • Autocomplete systems
  • Spell checkers
  • IP routing tables
  • Dictionary implementations
  • String matching
  • Word games

Time & Space Complexity

Operation Time Complexity Space Complexity
Insert O(m) O(m)
Search O(m) O(1)
Prefix Search O(p + n) O(1)
Delete O(m) O(1)

m = word length, p = prefix length, n = words with prefix

Strengths & Limitations

Strengths:

  • Fast prefix-based searches
  • Memory efficient for common prefixes
  • Supports autocomplete efficiently
  • No hash collisions

Limitations:

  • Memory overhead for sparse data
  • Cache performance issues
  • Complex implementation

Prefix Tree (Trie) Code Implementation

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