Word Search in Trie in DSA C++ - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to insert a character into the Trie node's children.

DSA C++

node->children[[1]] = new TrieNode();

Drag options to blanks, or click blank then click option'

A'c' - 'a'

B'b' - 'a'

C'z' - 'a'

D'a' - 'a'

Attempts:

3 left

💡 Hint

Common Mistakes

Using character directly without subtracting 'a'.

Using wrong character subtraction causing out of range index.

The character 'b' minus 'a' gives the correct index 1 for the children array.

2fill in blank

medium

Complete the code to check if the current Trie node marks the end of a word.

DSA C++

if (node->[1]) { return true; }

Drag options to blanks, or click blank then click option'

AwordEnd

BendOfWord

CisEnd

DisWord

Attempts:

3 left

💡 Hint

Common Mistakes

Using incorrect or undefined flag names.

Checking for null pointer instead of boolean flag.

The standard boolean flag used is 'isEnd' to mark the end of a word in the Trie node.

3fill in blank

hard

Fix the error in the search function to correctly traverse the Trie for each character.

DSA C++

node = node->children[[1]];

Drag options to blanks, or click blank then click option'

Aword[i] - 'a'

Bword[i]

Ci

D'a'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the character directly as index causing out of bounds.

Using the loop index 'i' as index instead of character mapping.

We must convert the character to an index by subtracting 'a' to access the correct child node.

4fill in blank

hard

Fill both blanks to complete the recursive helper function for word search in Trie.

DSA C++

bool searchHelper(TrieNode* node, const string& word, int [1]) {
    if ([2] == word.size()) return node->isEnd;
    int index = word[[1]] - 'a';
    if (!node->children[index]) return false;
    return searchHelper(node->children[index], word, [1] + 1);
}

Drag options to blanks, or click blank then click option'

Apos

Bindex

Dlength

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names causing mismatch.

Comparing wrong variable to word size.

The variable 'pos' is used to track the current position in the word for recursion.

5fill in blank

hard

Fill all three blanks to complete the insert function for adding a word to the Trie.

DSA C++

void insert(string word) {
    TrieNode* node = root;
    for (int [1] = 0; [2] < word.size(); [3]++) {
        int index = word[[2]] - 'a';
        if (!node->children[index]) {
            node->children[index] = new TrieNode();
        }
        node = node->children[index];
    }
    node->isEnd = true;
}

Drag options to blanks, or click blank then click option'

Ai

Dj

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names in loop causing errors.

Incorrect loop increment syntax.

The loop variable 'i' is used consistently for initialization, condition, and increment.

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