Autocomplete System with Trie in DSA C++ - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to declare the root node of the Trie.

DSA C++

struct TrieNode {
    TrieNode* children[26];
    bool isEndOfWord;

    TrieNode() {
        for (int i = 0; i < 26; i++) {
            children[i] = nullptr;
        }
        isEndOfWord = false;
    }
};

TrieNode* [1] = new TrieNode();

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

Aroot

Bnode

Chead

Dstart

Attempts:

3 left

💡 Hint

Common Mistakes

Using variable names that do not clearly represent the root node.

Not initializing the root node properly.

The root of the Trie is commonly named 'root' to represent the starting point of the Trie structure.

2fill in blank

medium

Complete the code to insert a character into the Trie children array.

DSA C++

void insertWord(TrieNode* root, const string& word) {
    TrieNode* current = root;
    for (char c : word) {
        int index = c - 'a';
        if (current->children[[1]] == nullptr) {
            current->children[index] = new TrieNode();
        }
        current = current->children[index];
    }
    current->isEndOfWord = true;
}

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

Ac

Bindex

C0

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the character 'c' directly as an index.

Using a fixed index like 0 instead of the calculated index.

The index variable holds the position in the children array corresponding to the character c.

3fill in blank

hard

Fix the error in the search function to correctly check if a word exists in the Trie.

DSA C++

bool searchWord(TrieNode* root, const string& word) {
    TrieNode* current = root;
    for (char c : word) {
        int index = c - 'a';
        if (current->children[[1]] == nullptr) {
            return false;
        }
        current = current->children[index];
    }
    return current->isEndOfWord;
}

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

Ac

B0

Cindex

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Checking children[c] instead of children[index].

Using a fixed index like 0.

The search must check the children array at the position given by index, which corresponds to the character c.

4fill in blank

hard

Fill both blanks to complete the recursive function that collects all words starting from a given Trie node.

DSA C++

void collectWords(TrieNode* node, string prefix, vector<string>& results) {
    if (node->[1]) {
        results.push_back(prefix);
    }
    for (int i = 0; i < 26; i++) {
        if (node->children[i] != nullptr) {
            collectWords(node->children[i], prefix + [2], results);
        }
    }
}

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

AisEndOfWord

B'a' + i

Cchar('a' + i)

Dchildren

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong member name for the end of word flag.

Appending an integer instead of a character to the prefix.

The function checks if the current node marks the end of a word using isEndOfWord, and appends the character corresponding to index i by converting 'a' + i to a char.

5fill in blank

hard

Fill both blanks to complete the autocomplete function that returns all words with a given prefix.

DSA C++

vector<string> autocomplete(TrieNode* root, const string& prefix) {
    TrieNode* current = root;
    for (char c : prefix) {
        int index = c - 'a';
        if (current->children[[1]] == nullptr) {
            return {};
        }
        current = current->children[index];
    }
    vector<string> results;
    collectWords(current, [2], results);
    return results;
}

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

Aindex

Bprefix

C""

Dcurrent

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong index to access children.

Passing an empty string instead of the prefix to collectWords.

Returning the wrong variable.

The function uses the index to traverse children, passes the prefix string to collectWords to start collecting words, and returns the results vector.

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