Autocomplete System with Trie in DSA C++ - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Trie Insert and Search

What is the output of the following C++ code that inserts words into a Trie and searches for a prefix?

DSA C++

#include <iostream>
#include <string>
using namespace std;

struct TrieNode {
    TrieNode* children[26] = {nullptr};
    bool isEnd = false;
};

class Trie {
public:
    TrieNode* root;
    Trie() { root = new TrieNode(); }

    void insert(string word) {
        TrieNode* node = root;
        for (char c : word) {
            int idx = c - 'a';
            if (!node->children[idx])
                node->children[idx] = new TrieNode();
            node = node->children[idx];
        }
        node->isEnd = true;
    }

    bool startsWith(string prefix) {
        TrieNode* node = root;
        for (char c : prefix) {
            int idx = c - 'a';
            if (!node->children[idx]) return false;
            node = node->children[idx];
        }
        return true;
    }
};

int main() {
    Trie trie;
    trie.insert("apple");
    trie.insert("app");
    cout << trie.startsWith("app") << endl;
    cout << trie.startsWith("apl") << endl;
    return 0;
}

A

1
0

B

0
1

C

1
1

D

0
0

💡 Hint

Check if the prefix exists in the Trie after inserting the words.

The prefix "app" exists because both "app" and "apple" were inserted, so startsWith("app") returns true (1). The prefix "apl" does not exist, so startsWith("apl") returns false (0).

🧠 Conceptual

intermediate

Understanding Trie Node Structure

Which of the following best describes the purpose of the 'isEnd' boolean in a Trie node?

A It counts how many words pass through this node.

B It marks the node as the end of a valid word stored in the Trie.

C It stores the character value of the node.

D It indicates if the node has any children nodes.

💡 Hint

Think about how the Trie knows when a word finishes.

The 'isEnd' boolean marks that the path from root to this node forms a complete valid word in the Trie.

🔧 Debug

advanced

Identify the Bug in Trie Search

What error will occur when running this code snippet for searching a word in a Trie?

DSA C++

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

// root is not initialized in constructor

A Returns false always

B Runs correctly and returns true or false

C Compilation error due to missing return statement

D Segmentation fault due to uninitialized root pointer

💡 Hint

Check if root pointer is properly set before use.

If root is not initialized (e.g., root = new TrieNode()), accessing root->children causes a segmentation fault (crash).

🚀 Application

advanced

Autocomplete Suggestions Using Trie

Given a Trie with words inserted, which approach correctly collects all words starting with a given prefix?

A Store all words in a list and search prefix using string matching

B Check all nodes in Trie and filter words starting with prefix

C Traverse to prefix node, then DFS to collect all words from there

D Use BFS from root to find prefix and return first matching word only

💡 Hint

Think about efficient traversal after locating prefix node.

After reaching the node representing the prefix, a depth-first search (DFS) collects all words below it efficiently.

❓ Predict Output

expert

Output of Trie Autocomplete Function

What is the output of this C++ code that inserts words and prints autocomplete suggestions for prefix "ca"?

DSA C++

#include <iostream>
#include <vector>
#include <string>
using namespace std;

struct TrieNode {
    TrieNode* children[26] = {nullptr};
    bool isEnd = false;
};

class Trie {
public:
    TrieNode* root;
    Trie() { root = new TrieNode(); }

    void insert(string word) {
        TrieNode* node = root;
        for (char c : word) {
            int idx = c - 'a';
            if (!node->children[idx])
                node->children[idx] = new TrieNode();
            node = node->children[idx];
        }
        node->isEnd = true;
    }

    void dfs(TrieNode* node, string prefix, vector<string>& results) {
        if (node->isEnd) results.push_back(prefix);
        for (int i = 0; i < 26; i++) {
            if (node->children[i]) {
                dfs(node->children[i], prefix + char('a' + i), results);
            }
        }
    }

    vector<string> autocomplete(string prefix) {
        TrieNode* node = root;
        for (char c : prefix) {
            int idx = c - 'a';
            if (!node->children[idx]) return {};
            node = node->children[idx];
        }
        vector<string> results;
        dfs(node, prefix, results);
        return results;
    }
};

int main() {
    Trie trie;
    trie.insert("cat");
    trie.insert("car");
    trie.insert("cart");
    trie.insert("dog");
    vector<string> res = trie.autocomplete("ca");
    for (string s : res) cout << s << " ";
    return 0;
}

A car cart cat

B cart car cat

C cat car cart

D dog

💡 Hint

Check the order of DFS traversal over children nodes.

DFS visits children in alphabetical order (a to z). From prefix "ca", the node has children 'r' (index 17) and 't' (index 19). The loop processes 'r' first, collecting "car" and "cart", then 't', collecting "cat". Thus, the order is "car", "cart", "cat".

Practice

1. What is the main purpose of using a Trie in an autocomplete system?

easy

A. To efficiently store and search prefixes of words

B. To sort words alphabetically

C. To store words in a linked list

D. To perform arithmetic operations on words

Solution

1. Step 1: Understand the role of Trie in prefix search

   A Trie is a tree-like data structure that stores characters of words in a way that common prefixes share nodes.

2. Step 2: Connect Trie usage to autocomplete

   Autocomplete requires quick lookup of words starting with a given prefix, which Trie supports efficiently by traversing prefix nodes.

3. Final Answer:

   To efficiently store and search prefixes of words -> Option A

4. Quick Check:

   Trie = prefix search [OK]

Hint: Trie is all about prefix matching fast [OK]

Common Mistakes:

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

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

easy

A. class TrieNode { public: map children; bool isEnd; };

B. class TrieNode { int children[26]; bool isEnd; };

C. class TrieNode { public: TrieNode* children[26]; bool isEnd; TrieNode() { for(int i=0; i<26; i++) children[i] = nullptr; isEnd = false; } };

D. struct TrieNode { vector<int> children; bool isEnd; };

Solution

1. Step 1: Check for pointer array initialization

   class TrieNode { public: TrieNode* children[26]; bool isEnd; TrieNode() { for(int i=0; i<26; i++) children[i] = nullptr; isEnd = false; } }; correctly declares an array of 26 pointers to TrieNode, initialized to nullptr, representing children for each alphabet letter.

2. Step 2: Verify isEnd boolean initialization

   class TrieNode { public: TrieNode* children[26]; bool isEnd; TrieNode() { for(int i=0; i<26; i++) children[i] = nullptr; isEnd = false; } }; sets isEnd to false in constructor, which marks if a word ends at this node.

3. Final Answer:

   class TrieNode { public: TrieNode* children[26]; bool isEnd; TrieNode() { for(int i=0; i<26; i++) children[i] = nullptr; isEnd = false; } }; -> Option C

4. Quick Check:

   Pointer array + bool flag = class TrieNode { public: TrieNode* children[26]; bool isEnd; TrieNode() { for(int i=0; i<26; i++) children[i] = nullptr; isEnd = false; } }; [OK]

Hint: Trie nodes use pointer arrays for children [OK]

Common Mistakes:

• Using int array instead of pointer array
• Not initializing children pointers
• Using map<int> instead of map<char>

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

class TrieNode {
public:
    TrieNode* children[26];
    bool isEnd;
    TrieNode() {
        for(int i=0; i<26; i++) children[i] = nullptr;
        isEnd = false;
    }
};

class Trie {
public:
    TrieNode* root;
    Trie() { root = new TrieNode(); }

    void insert(string word) {
        TrieNode* node = root;
        for(char c : word) {
            int idx = c - 'a';
            if(!node->children[idx])
                node->children[idx] = new TrieNode();
            node = node->children[idx];
        }
        node->isEnd = true;
    }

    bool startsWith(string prefix) {
        TrieNode* node = root;
        for(char c : prefix) {
            int idx = c - 'a';
            if(!node->children[idx]) return false;
            node = node->children[idx];
        }
        return true;
    }
};

int main() {
    Trie trie;
    trie.insert("apple");
    trie.insert("app");
    cout << (trie.startsWith("app") ? "Yes" : "No") << endl;
    cout << (trie.startsWith("apl") ? "Yes" : "No") << endl;
    return 0;
}

medium

A. No
Yes

B. Yes
No

C. Yes
Yes

D. No
No

Solution

1. Step 1: Insert words "apple" and "app" into Trie

   Both words share prefix "app", so nodes for 'a', 'p', 'p' exist. "apple" adds nodes for 'l' and 'e'.

2. Step 2: Check startsWith for "app" and "apl"

   "app" prefix exists, so returns true (prints "Yes"). "apl" prefix does not exist (no 'l' after 'p'), so returns false (prints "No").

3. Final Answer:

   Yes No -> Option B

4. Quick Check:

   Prefix "app" found, "apl" not found = Yes No [OK]

Hint: Check prefix nodes existence for startsWith [OK]

Common Mistakes:

• Confusing isEnd with prefix existence
• Assuming "apl" is found because 'a' and 'p' exist
• Printing boolean instead of Yes/No

4. Identify the bug in this Trie insertion code snippet:

void insert(string word) {
    TrieNode* node = root;
    for(char c : word) {
        int idx = c - 'a';
        if(node->children[idx] == nullptr)
            node->children[idx] = new TrieNode();
        node = node->children[idx];
        node->isEnd = true;
    }
}

medium

A. Setting isEnd = true inside the loop causes all prefixes to be marked as words

B. Not initializing children array to nullptr

C. Missing root initialization

D. Incorrect index calculation for children array

Solution

1. Step 1: Analyze isEnd assignment inside loop

   Setting isEnd = true inside the loop marks every node along the word as an end of a word, incorrectly marking prefixes as complete words.

2. Step 2: Correct placement of isEnd assignment

   isEnd should be set to true only after the loop ends, marking only the last node as end of the inserted word.

3. Final Answer:

   Setting isEnd = true inside the loop causes all prefixes to be marked as words -> Option A

4. Quick Check:

   isEnd inside loop = wrong word marking [OK]

Hint: Set isEnd true only after full word insertion [OK]

Common Mistakes:

• Marking prefixes as complete words
• Forgetting to set isEnd at all
• Incorrect children pointer checks

5. You want to implement an autocomplete system that returns all words starting with a given prefix using a Trie. Which approach correctly retrieves all such words?

hard

A. Use a hash map to store prefix to word list mapping directly

B. Store all words in a vector and filter by prefix each time

C. Traverse Trie and return words only if isEnd is true at prefix node

D. Traverse Trie to prefix node, then perform DFS to collect all words below it

Solution

1. Step 1: Locate prefix node in Trie

   Traverse the Trie character by character to reach the node representing the last character of the prefix.

2. Step 2: Perform DFS from prefix node to collect words

   From this node, recursively explore all child nodes to find all words that start with the prefix, collecting those where isEnd is true.

3. Final Answer:

   Traverse Trie to prefix node, then perform DFS to collect all words below it -> Option D

4. Quick Check:

   Prefix node + DFS = all autocomplete words [OK]

Hint: Find prefix node, then DFS to get all words [OK]

Common Mistakes:

• Returning only prefix node word ignoring children
• Filtering all words each query (inefficient)
• Using hash map without Trie traversal