Prefix Search Using Trie in DSA Java - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Prefix Search Result

What is the output of the following Java code that inserts words into a Trie and searches for words with a given prefix?

DSA Java

class TrieNode {
    TrieNode[] children = new TrieNode[26];
    boolean isEnd = false;
}

class Trie {
    TrieNode root = new TrieNode();

    void insert(String word) {
        TrieNode node = root;
        for (char c : word.toCharArray()) {
            int idx = c - 'a';
            if (node.children[idx] == null) {
                node.children[idx] = new TrieNode();
            }
            node = node.children[idx];
        }
        node.isEnd = true;
    }

    boolean startsWith(String prefix) {
        TrieNode node = root;
        for (char c : prefix.toCharArray()) {
            int idx = c - 'a';
            if (node.children[idx] == null) return false;
            node = node.children[idx];
        }
        return true;
    }
}

public class Main {
    public static void main(String[] args) {
        Trie trie = new Trie();
        trie.insert("apple");
        trie.insert("app");
        trie.insert("bat");
        trie.insert("bath");
        System.out.println(trie.startsWith("app"));
        System.out.println(trie.startsWith("bat"));
        System.out.println(trie.startsWith("bath"));
        System.out.println(trie.startsWith("batman"));
    }
}

A

true
true
true
false

B

true
true
false
false

C

false
true
true
false

D

true
false
true
false

💡 Hint

Check if the prefix exists by traversing the Trie nodes for each character.

The method startsWith returns true if the prefix exists in the Trie. The prefixes "app", "bat", and "bath" exist, but "batman" does not.

🧠 Conceptual

intermediate

Number of Children in Trie Node

In a Trie node designed for lowercase English letters, how many children pointers does each node have?

A 128

B 26

C 10

D 52

💡 Hint

Think about the number of lowercase English alphabets.

Each Trie node has 26 children pointers, one for each lowercase English letter from 'a' to 'z'.

🔧 Debug

advanced

Identify the Bug in Trie Insert Method

What error will occur when running the following insert method in a Trie if the input word contains uppercase letters?

DSA Java

void insert(String word) {
    TrieNode node = root;
    for (char c : word.toCharArray()) {
        int idx = c - 'a';
        if (node.children[idx] == null) {
            node.children[idx] = new TrieNode();
        }
        node = node.children[idx];
    }
    node.isEnd = true;
}

A ArrayIndexOutOfBoundsException

B NullPointerException

C No error, works fine

D ClassCastException

💡 Hint

Check how the index is calculated for uppercase letters.

Uppercase letters have ASCII values less than 'a', so subtracting 'a' results in a negative index, causing ArrayIndexOutOfBoundsException.

🚀 Application

advanced

Count Words with Given Prefix Using Trie

Given a Trie with inserted words, which approach correctly counts how many words start with a given prefix?

A Return the number of children of the root node.

B Count all nodes in the Trie regardless of prefix.

C Traverse to the prefix node, then recursively count all nodes marked as word ends in its subtree.

D Count only the prefix node without checking descendants.

💡 Hint

Think about how to find all words starting with the prefix.

To count words with a prefix, first find the node representing the prefix, then count all complete words in its subtree.

❓ Predict Output

expert

Output of Trie Search After Multiple Inserts

What is the output of the following Java code that inserts words and searches for prefixes?

DSA Java

class TrieNode {
    TrieNode[] children = new TrieNode[26];
    boolean isEnd = false;
}

class Trie {
    TrieNode root = new TrieNode();

    void insert(String word) {
        TrieNode node = root;
        for (char c : word.toCharArray()) {
            int idx = c - 'a';
            if (node.children[idx] == null) {
                node.children[idx] = new TrieNode();
            }
            node = node.children[idx];
        }
        node.isEnd = true;
    }

    boolean search(String word) {
        TrieNode node = root;
        for (char c : word.toCharArray()) {
            int idx = c - 'a';
            if (node.children[idx] == null) return false;
            node = node.children[idx];
        }
        return node.isEnd;
    }
}

public class Main {
    public static void main(String[] args) {
        Trie trie = new Trie();
        trie.insert("cat");
        trie.insert("car");
        trie.insert("cart");
        trie.insert("dog");
        System.out.println(trie.search("car"));
        System.out.println(trie.search("cart"));
        System.out.println(trie.search("cat"));
        System.out.println(trie.search("ca"));
        System.out.println(trie.search("dog"));
        System.out.println(trie.search("do"));
    }
}

A

true
true
false
false
true
false

B

true
false
true
false
true
false

C

false
true
true
false
true
false

D

true
true
true
false
true
false

💡 Hint

Check if the search method returns true only for complete words inserted.

The search method returns true only if the word is fully present and marked as an end. "ca" and "do" are prefixes but not complete words, so false.

Practice

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

easy

A. To efficiently find all words that start with a given prefix

B. To sort words alphabetically

C. To store numbers in sorted order

D. To perform arithmetic operations quickly

Solution

1. Step 1: Understand what prefix search means

   Prefix search means finding all words that start with a certain beginning sequence of letters.

2. Step 2: Understand Trie's role in prefix search

   A Trie stores words in a tree where each node represents a letter, making it easy to find all words sharing the same prefix by traversing the tree.

3. Final Answer:

   To efficiently find all words that start with a given prefix -> Option A

4. Quick Check:

   Prefix search = efficient word lookup [OK]

Hint: Trie nodes represent letters for fast prefix lookup [OK]

Common Mistakes:

• Confusing Trie with sorting data structures
• Thinking Trie is for arithmetic operations
• Assuming Trie stores numbers only

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

easy

A. class TrieNode { int[] children = new int[26]; boolean isEndOfWord; }

B. class TrieNode { char[] children = new char[26]; boolean isEndOfWord; }

C. class TrieNode { String[] children = new String[26]; boolean isEndOfWord; }

D. class TrieNode { TrieNode[] children = new TrieNode[26]; boolean isEndOfWord; }

Solution

1. Step 1: Identify the correct type for children nodes

   Each child should be a reference to another TrieNode, so the array type must be TrieNode[].

2. Step 2: Check the other parts of the class

   Boolean isEndOfWord marks if the node ends a word, which is correct in class TrieNode { TrieNode[] children = new TrieNode[26]; boolean isEndOfWord; }.

3. Final Answer:

   class TrieNode { TrieNode[] children = new TrieNode[26]; boolean isEndOfWord; } -> Option D

4. Quick Check:

   Children are TrieNode references [OK]

Hint: Children array holds TrieNode references, not primitives [OK]

Common Mistakes:

• Using int or char arrays instead of TrieNode array
• Using String array for children
• Forgetting to mark end of word

3. Given the following code snippet, what will be the output?

Trie trie = new Trie();
trie.insert("cat");
trie.insert("car");
trie.insert("dog");
System.out.println(trie.startsWith("ca"));
System.out.println(trie.startsWith("do"));
System.out.println(trie.startsWith("bat"));

medium

A. true
true
false

B. true
false
false

C. false
true
false

D. false
false
true

Solution

1. Step 1: Insert words into the Trie

   Words "cat", "car", and "dog" are inserted, so prefixes "ca" and "do" exist in the Trie.

2. Step 2: Check startsWith results

   startsWith("ca") returns true because "cat" and "car" start with "ca".
   startsWith("do") returns true because "dog" starts with "do".
   startsWith("bat") returns false because no word starts with "bat".

3. Final Answer:

   true true false -> Option A

4. Quick Check:

   Prefix "ca" and "do" found, "bat" not found [OK]

Hint: Check inserted words' prefixes carefully [OK]

Common Mistakes:

• Assuming startsWith returns false if word not complete
• Confusing startsWith with search for whole word
• Mixing up true/false outputs

4. The following Java method is intended to check if a prefix exists in a Trie, but it has a bug. What is the bug?

public boolean startsWith(String prefix) {
    TrieNode node = root;
    for (int i = 0; i <= prefix.length(); i++) {
        char c = prefix.charAt(i);
        if (node.children[c - 'a'] == null) return false;
        node = node.children[c - 'a'];
    }
    return true;
}

medium

A. The root node is not initialized before the loop

B. The loop condition should be < instead of <= to avoid IndexOutOfBoundsException

C. The method should return false at the end instead of true

D. The character indexing is wrong; should use c + 'a'

Solution

1. Step 1: Analyze the for-loop condition

   The loop runs from i = 0 to i <= prefix.length(), which means it tries to access prefix.charAt(prefix.length()), causing an IndexOutOfBoundsException.

2. Step 2: Correct the loop condition

   The loop should run while i < prefix.length() to access valid characters only.

3. Final Answer:

   The loop condition should be < instead of <= to avoid IndexOutOfBoundsException -> Option B

4. Quick Check:

   Loop index must be less than length [OK]

Hint: Loop index must be less than string length [OK]

Common Mistakes:

• Using <= instead of < in loop condition
• Incorrect character arithmetic
• Returning wrong boolean at the end

5. You want to find all words in a Trie that start with the prefix "app". Which approach correctly retrieves all such words?

hard

A. Use a hash map to store all words and filter those starting with "app"

B. Search each word in the Trie individually to check if it starts with "app"

C. Traverse the Trie to the node representing 'p' in "app", then perform a depth-first search collecting all words below

D. Insert "app" as a word and then search for it

Solution

1. Step 1: Locate the prefix node in the Trie

   Traverse the Trie following letters 'a', 'p', 'p' to reach the node representing the last 'p' in "app".

2. Step 2: Collect all words below this node

   Perform a depth-first search (DFS) from this node to find all complete words that start with "app".

3. Final Answer:

   Traverse the Trie to the node representing 'p' in "app", then perform a depth-first search collecting all words below -> Option C

4. Quick Check:

   Prefix node + DFS = all matching words [OK]

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

Common Mistakes:

• Checking all words instead of using Trie structure
• Using hash map instead of Trie traversal
• Confusing insertion with search