Interactive simulator for Trie (prefix tree) data structure. Build a dictionary, search by prefix, and see how Trie enables efficient autocomplete functionality. Understand the tree structure and prefix matching algorithm.
Why simulate Trie?
Trie is a powerful data structure for prefix-based searches. This simulator helps you understand how Trie organizes words, how prefix matching works, and why it's so efficient for autocomplete features.
How Trie works
Trie stores words as a tree where each node represents a character. Words sharing a common prefix share the same path in the tree. This makes prefix searches extremely fast—O(m) where m is the prefix length.
Good for
- Understand prefix search algorithms
- Visualize autocomplete functionality
- Learn Trie data structure
- Test search performance
Questions people ask
What is a Trie?
A Trie (prefix tree) is a tree data structure that stores strings by organizing them character by character. Words with common prefixes share nodes, making prefix searches very efficient.
When should I use Trie?
Trie is ideal for autocomplete, spell checkers, IP routing, and any application requiring fast prefix matching. It's used in search engines, IDEs, and routing tables.