DSA Masterclass Module 14: Tries & Advanced Structures

Introduction to Tries

A Trie (pronounced "try") or Prefix Tree is a specialized tree structure used for storing strings. Unlike a standard search tree, nodes in a trie don't store their associated key; instead, their position in the tree defines the string.

1. Real-World Intuition: Autocomplete

Imagine typing "Go" into Google.

The system doesn't search every word in the dictionary.
it starts at a root node, moves to 'G', then to 'o'.
It then looks at all children of 'o' and returns the most frequent ones (Google, Go, Golang).

2. Curriculum in this Module

Theory & Intuition (Current Page)
Lesson: Trie Implementation - Building insert, search, and startsWith.
Problem: Word Search II - Combining Tries with Matrix Backtracking.
Curated Practice Problems - 10 essential challenges.

3. The Trie Node Anatomy

Each node typically contains:

children[]: An array of size 26 (for 'a'-'z').
isEndOfWord: A boolean flag to mark a complete string.

class TrieNode {
    TrieNode[] children = new TrieNode[26];
    boolean isEndOfWord = false;
}

Final Takeaway

Tries trade Space for Time. They use more memory than HashMaps but provide strictly $O(L)$ lookups for prefixes, where $L$ is the string length.