Trie Pattern

When to use Trie

• You need to answer many prefix queries against a fixed dictionary (autocomplete, spell check, longest prefix match).
• You are searching a board or grid for any word from a list — a trie lets you abandon a path the moment the prefix is no longer in the dictionary.
• You need a fast 'word exists' or 'prefix exists' check across a large word list, where a hash set would lose the prefix structure.
• The problem asks for the shortest unique prefix, longest common prefix, or words that share a stem.
• You need to support insertions and deletions on a string set with stable O(L) cost regardless of dictionary size.

Template

class TrieNode {
  constructor() {
    this.children = new Map();
    this.isWord = false;
  }
}

class Trie {
  constructor() {
    this.root = new TrieNode();
  }
  insert(word) {
    let node = this.root;
    for (const ch of word) {
      if (!node.children.has(ch)) node.children.set(ch, new TrieNode());
      node = node.children.get(ch);
    }
    node.isWord = true;
  }
  search(word) {
    let node = this.root;
    for (const ch of word) {
      if (!node.children.has(ch)) return false;
      node = node.children.get(ch);
    }
    return node.isWord;
  }
}

Common mistakes

• Forgetting to set isWord (or the equivalent terminal flag) at the final node, so search() returns false for inserted words.
• Reusing a single TrieNode object instance across multiple children due to a default-argument bug or shared mutable default, which corrupts the entire tree.
• On Word Search II, building the trie but still issuing one DFS per dictionary word instead of a single board-wide DFS that walks the trie alongside the grid.
• Storing children in a fixed-size 26-element array even when the input includes uppercase, digits, or unicode — collisions truncate the trie silently.
• Failing to prune visited dictionary words after a match in Word Search II, which produces duplicate entries in the output list.