Word Search in Trie in DSA Go

Mental Model

A trie stores words by sharing common prefixes, making it easy to check if a word exists by following letters step-by-step.

Analogy: Imagine a tree of roads where each road sign is a letter. To find a word, you follow the signs letter by letter until you reach the end of the word.

root
 ↓
 a -> b -> c (end)
  ↓
  d (end)

Each arrow -> shows the next letter link.
'end' marks a complete word.

Dry Run Walkthrough

Input: Insert words: "cat", "car", "dog"; Search for "car"

Goal: Check if the word "car" exists in the trie

Step 1: Insert 'cat' letter by letter

root -> c -> a -> t [end]
root -> null

Why: Build path for 'cat' so we can find it later

Step 2: Insert 'car' letter by letter, sharing prefix 'ca'

root -> c -> a -> t [end]
               ↓
               r [end]

Why: Reuse 'ca' nodes, add 'r' to mark 'car'

Step 3: Insert 'dog' letter by letter

root -> c -> a -> t [end]
               ↓
               r [end]
root -> d -> o -> g [end]

Why: Add new branch for 'dog'

Step 4: Search for 'car' by following letters c -> a -> r

root -> c -> a -> r [end]

Why: All letters found and 'r' marks end of word, so 'car' exists

Result:

root -> c -> a -> t [end]
               ↓
               r [end]
root -> d -> o -> g [end]
Search result: true

Annotated Code

DSA Go

package main

import "fmt"

// TrieNode represents each node in the trie
type TrieNode struct {
	children map[rune]*TrieNode
	isEnd bool
}

// Trie structure with root node
type Trie struct {
	root *TrieNode
}

// NewTrieNode creates a new trie node
func NewTrieNode() *TrieNode {
	return &TrieNode{children: make(map[rune]*TrieNode)}
}

// NewTrie creates a new trie
func NewTrie() *Trie {
	return &Trie{root: NewTrieNode()}
}

// Insert adds a word to the trie
func (t *Trie) Insert(word string) {
	curr := t.root
	for _, ch := range word {
		if _, ok := curr.children[ch]; !ok {
			curr.children[ch] = NewTrieNode() // create node if missing
		}
		curr = curr.children[ch] // move to next node
	}
	curr.isEnd = true // mark end of word
}

// Search checks if a word exists in the trie
func (t *Trie) Search(word string) bool {
	curr := t.root
	for _, ch := range word {
		if _, ok := curr.children[ch]; !ok {
			return false // letter missing, word not found
		}
		curr = curr.children[ch] // move to next node
	}
	return curr.isEnd // true if end of word
}

func main() {
	trie := NewTrie()
	trie.Insert("cat")
	trie.Insert("car")
	trie.Insert("dog")

	fmt.Println(trie.Search("car"))
}

if _, ok := curr.children[ch]; !ok {

check if current letter node exists

curr.children[ch] = NewTrieNode() // create node if missing

create new node for letter if missing

curr = curr.children[ch] // move to next node

advance current pointer to next letter node

curr.isEnd = true // mark end of a complete word

mark node as end of a complete word

if _, ok := curr.children[ch]; !ok { return false }

if letter missing during search, word not found

return curr.isEnd // true if end of word

return true only if last letter marks word end

Output

true

Complexity Analysis

Time: O(m) because we process each of the m letters in the word once during insert or search

Space: O(m) for insert because new nodes may be created for each letter; search uses O(1) extra space

vs Alternative: Compared to searching in a list of words (O(n*m)), trie search is faster as it avoids scanning all words

Edge Cases

search for empty string

returns false because empty word is not inserted

DSA Go

return curr.isEnd // true if end of word

search for word not inserted

returns false as missing letter node detected

DSA Go

if _, ok := curr.children[ch]; !ok { return false }

insert duplicate word

no new nodes created, end marker remains true

DSA Go

curr.isEnd = true // mark end of word

When to Use This Pattern

When you need to quickly check if words or prefixes exist in a large set, use a trie because it shares common prefixes and speeds up search.

Common Mistakes

Mistake: Not marking the end of a word, causing search to return true for prefixes instead of full words
Fix: Always set isEnd = true at the last node of inserted words

Mistake: Not checking if a child node exists before moving, causing runtime errors
Fix: Check if child node exists before moving; if missing, create node (insert) or return false (search)

Summary

Stores words letter by letter sharing prefixes to enable fast word search.

Use when you want to check if words exist efficiently among many words.

The key is to follow letters step-by-step and mark where words end.