Word Search in Trie in DSA C++ - Build from Scratch

Word Search in Trie

📖 Scenario: Imagine you have a small dictionary of words and you want to quickly check if a word exists in it. A Trie is a tree-like data structure that helps you do this efficiently.In this project, you will build a simple Trie with a few words and then search for a specific word in it.

🎯 Goal: You will create a Trie with given words, set up a search word, write the search logic to check if the word exists in the Trie, and finally print the result.

📋 What You'll Learn

Create a TrieNode class with an array of 26 children pointers and a boolean to mark end of word

Insert given words into the Trie

Create a string variable for the word to search

Write a function to search the word in the Trie

Print 'Found' if the word exists, otherwise print 'Not Found'

💡 Why This Matters

🌍 Real World

Tries are used in autocomplete systems, spell checkers, and IP routing to quickly find words or prefixes.

💼 Career

Understanding Tries helps in software engineering roles involving text processing, search engines, and efficient data retrieval.

1

Create TrieNode class and insert words

Create a class called TrieNode with a public boolean isEndOfWord initialized to false and an array of 26 TrieNode* pointers called children initialized to nullptr. Then create a class called Trie with a public TrieNode* called root initialized to a new TrieNode. Finally, write a public method insert in Trie that takes a const string& called word and inserts it into the Trie by creating nodes for each character.

DSA C++

#include 
#include 
using namespace std;

// Create TrieNode class and Trie class with insert method
// Your code here

Hint

Remember to initialize all children pointers to nullptr in the TrieNode constructor.

In the insert method, create new nodes only if the child pointer is nullptr.

2

Set the word to search

Create a string variable called searchWord and set it to "cat".

DSA C++

#include 
#include 
using namespace std;

class TrieNode {
public:
    bool isEndOfWord;
    TrieNode* children[26];
    TrieNode() {
        isEndOfWord = false;
        for (int i = 0; i children[index] == nullptr) {
                node->children[index] = new TrieNode();
            }
            node = node->children[index];
        }
        node->isEndOfWord = true;
    }
};

// Create string variable searchWord and set it to "cat"
// Your code here

Hint

Just create a string variable named searchWord and assign it the value "cat".

3

Write search function in Trie

Add a public method bool search(const string& word) in the Trie class that returns true if the word exists in the Trie and false otherwise. Use a loop to traverse the Trie nodes for each character. Return node->isEndOfWord at the end.

DSA C++

#include 
#include 
using namespace std;

class TrieNode {
public:
    bool isEndOfWord;
    TrieNode* children[26];
    TrieNode() {
        isEndOfWord = false;
        for (int i = 0; i children[index] == nullptr) {
                node->children[index] = new TrieNode();
            }
            node = node->children[index];
        }
        node->isEndOfWord = true;
    }

    // Add search method here
    // Your code here
};

string searchWord = "cat";

Hint

Traverse the Trie nodes for each character in the word.

If any character node is missing, return false.

At the end, return node->isEndOfWord to confirm the word exists.

4

Insert words, search and print result

Create a Trie object called trie. Insert the words "cat", "car", and "dog" into trie using the insert method. Then use the search method to check if searchWord exists in the Trie. Print "Found" if it exists, otherwise print "Not Found".

DSA C++

#include 
#include 
using namespace std;

class TrieNode {
public:
    bool isEndOfWord;
    TrieNode* children[26];
    TrieNode() {
        isEndOfWord = false;
        for (int i = 0; i children[index] == nullptr) {
                node->children[index] = new TrieNode();
            }
            node = node->children[index];
        }
        node->isEndOfWord = true;
    }

    bool search(const string& word) {
        TrieNode* node = root;
        for (char ch : word) {
            int index = ch - 'a';
            if (node->children[index] == nullptr) {
                return false;
            }
            node = node->children[index];
        }
        return node->isEndOfWord;
    }
};

string searchWord = "cat";

// Create Trie object trie
// Insert "cat", "car", "dog" into trie
// Search for searchWord and print "Found" or "Not Found"
// Your code here

Hint

Create a Trie object named trie.

Insert the words "cat", "car", and "dog" using trie.insert().

Use trie.search(searchWord) to check if the word exists.

Print "Found" if true, otherwise "Not Found".

Practice

1. What is the main purpose of using a Trie data structure in word search problems?

easy

A. To store words in a linked list

B. To sort words alphabetically

C. To efficiently store and search words by their prefixes

D. To perform arithmetic operations on words

Solution

1. Step 1: Understand Trie structure

   A Trie stores characters of words in a tree where each node represents a character, allowing prefix sharing.

2. Step 2: Identify Trie use in word search

   Because words share prefixes, Trie allows fast prefix-based search, making word search efficient.

3. Final Answer:

   To efficiently store and search words by their prefixes -> Option C

4. Quick Check:

   Trie = prefix search [OK]

Hint: Trie is best for prefix-based word search [OK]

Common Mistakes:

• Confusing Trie with sorting structures
• Thinking Trie stores words linearly
• Assuming Trie is for arithmetic

2. Which of the following is the correct way to declare a Trie node class in C++ for word search?

easy

A. class TrieNode { public: TrieNode* children[26]; bool isEndOfWord; };

B. class TrieNode { int data; TrieNode* next; };

C. struct TrieNode { vector<int> children; bool end; };

D. class TrieNode { char letter; TrieNode* left; TrieNode* right; };

Solution

1. Step 1: Check Trie node structure for word search

   Trie nodes typically have an array of pointers for 26 letters and a boolean to mark word end.

2. Step 2: Match with options

   class TrieNode { public: TrieNode* children[26]; bool isEndOfWord; }; matches this structure exactly with children array and isEndOfWord flag.

3. Final Answer:

   class TrieNode { public: TrieNode* children[26]; bool isEndOfWord; }; -> Option A

4. Quick Check:

   Trie node = children array + end flag [OK]

Hint: Trie nodes have 26 children pointers and end flag [OK]

Common Mistakes:

• Using linked list pointers instead of array
• Using vector<int> instead of pointers
• Confusing binary tree node with Trie node

3. What will be the output of the following C++ code snippet that inserts words into a Trie and searches for "cat"?

class TrieNode {
public:
    TrieNode* children[26] = {nullptr};
    bool isEndOfWord = false;
};

class Trie {
public:
    TrieNode* root;
    Trie() { root = new TrieNode(); }
    void insert(string word) {
        TrieNode* node = root;
        for (char c : word) {
            int index = c - 'a';
            if (!node->children[index])
                node->children[index] = new TrieNode();
            node = node->children[index];
        }
        node->isEndOfWord = true;
    }
    bool search(string word) {
        TrieNode* node = root;
        for (char c : word) {
            int index = c - 'a';
            if (!node->children[index])
                return false;
            node = node->children[index];
        }
        return node->isEndOfWord;
    }
};

int main() {
    Trie trie;
    trie.insert("cat");
    trie.insert("car");
    trie.insert("dog");
    cout << (trie.search("cat") ? "Found" : "Not Found") << endl;
    return 0;
}

medium

A. Runtime Error

B. Found

C. Compilation Error

D. Not Found

Solution

1. Step 1: Insert words "cat", "car", "dog" into Trie

   Each word is inserted character by character, creating nodes and marking end of word for last character.

2. Step 2: Search for "cat" in Trie

   Traversal finds nodes for 'c', 'a', 't' and confirms isEndOfWord is true, so returns true.

3. Final Answer:

   Found -> Option B

4. Quick Check:

   Inserted word found = Found [OK]

Hint: Search returns true if end flag is set after traversal [OK]

Common Mistakes:

• Not marking isEndOfWord true on insert
• Returning true without checking end flag
• Off-by-one errors in indexing

4. Identify the bug in the following Trie search function and select the correct fix:

bool search(string word) {
    TrieNode* node = root;
    for (char c : word) {
        int index = c - 'a';
        if (node->children[index])
            return false;
        node = node->children[index];
    }
    return node->isEndOfWord;
}

medium

A. Add a check for null root pointer before loop

B. Remove the return statement inside the loop

C. Change 'node = node->children[index];' to 'node = node->children[index + 1];'

D. Change 'if (node->children[index])' to 'if (!node->children[index])'

Solution

1. Step 1: Analyze the if condition inside loop

   The condition 'if (node->children[index]) return false;' wrongly returns false if child exists, which is opposite logic.

2. Step 2: Correct the condition to check if child does NOT exist

   It should be 'if (!node->children[index]) return false;' to return false when path breaks.

3. Final Answer:

   Change 'if (node->children[index])' to 'if (!node->children[index])' -> Option D

4. Quick Check:

   Check for missing child = return false [OK]

Hint: Return false if child node is missing, not if present [OK]

Common Mistakes:

• Returning false when child exists
• Ignoring null pointer checks
• Incorrect index calculation

5. Given a list of words: ["apple", "app", "application", "bat", "bath", "batman"], how can a Trie be used to efficiently find all words starting with the prefix "app"? Choose the best approach.

hard

A. Insert all words into Trie, then traverse nodes for 'a'->'p'->'p' and collect all descendant words

B. Sort the list and perform binary search for prefix "app"

C. Use a hash map to store all words and check prefix by substring

D. Store words in a linked list and scan each word for prefix match

Solution

1. Step 1: Insert all words into Trie

   Each word is inserted character by character, building a prefix tree.

2. Step 2: Traverse Trie nodes for prefix "app"

   Follow nodes for 'a', 'p', 'p' to reach prefix node, then collect all words below it.

3. Step 3: Collect descendant words

   Perform DFS or BFS from prefix node to gather all words starting with "app" efficiently.

4. Final Answer:

   Insert all words into Trie, then traverse nodes for 'a'->'p'->'p' and collect all descendant words -> Option A

5. Quick Check:

   Trie prefix traversal + collect descendants = Insert all words into Trie, then traverse nodes for 'a'->'p'->'p' and collect all descendant words [OK]

Hint: Traverse prefix nodes then gather descendants in Trie [OK]

Common Mistakes:

• Using sorting instead of Trie for prefix search
• Checking prefix by substring on all words
• Scanning linked list inefficiently