Word Search in Trie in DSA Java - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a new TrieNode.

DSA Java

class TrieNode {
    boolean isWord;
    TrieNode[] children = new TrieNode[26];

    public TrieNode() {
        isWord = [1];
    }
}

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

Anull

Bfalse

Ctrue

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Setting isWord to true by default, which incorrectly marks all nodes as word ends.

When creating a new TrieNode, isWord should be false initially because no word ends at this node yet.

2fill in blank

medium

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

DSA Java

public void insert(String word) {
    TrieNode node = root;
    for (char c : word.toCharArray()) {
        int index = c - 'a';
        if (node.children[[1]] == null) {
            node.children[index] = new TrieNode();
        }
        node = node.children[index];
    }
    node.isWord = true;
}

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

Ac

Bword

Cnode

Dindex

Attempts:

3 left

💡 Hint

Common Mistakes

Using the character c directly as an index, which causes errors.

Using the node or word variable incorrectly as an index.

We use the integer index calculated from the character to access the correct child node.

3fill in blank

hard

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

DSA Java

public boolean search(String word) {
    TrieNode node = root;
    for (char c : word.toCharArray()) {
        int index = c - 'a';
        if (node.children[index] == null) {
            return [1];
        }
        node = node.children[index];
    }
    return node.isWord;
}

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

Afalse

Btrue

Cnull

Dnode == null

Attempts:

3 left

💡 Hint

Common Mistakes

Returning true when the path is missing, causing false positives.

Returning null or checking node == null incorrectly.

If a character path is missing, the word does not exist, so return false.

4fill in blank

hard

Fill both blanks to implement a method that checks if any word starts with a given prefix.

DSA Java

public boolean startsWith(String prefix) {
    TrieNode node = root;
    for (char c : prefix.toCharArray()) {
        int index = c - 'a';
        if (node.children[[1]] == null) {
            return [2];
        }
        node = node.children[index];
    }
    return true;
}

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

Aindex

Btrue

Cfalse

Dc

Attempts:

3 left

💡 Hint

Common Mistakes

Using character c directly as index.

Returning true when the path is missing.

We check the child at index and return false if missing, otherwise true if prefix exists.

5fill in blank

hard

Fill all three blanks to implement a method that deletes a word from the Trie recursively.

DSA Java

private boolean delete(TrieNode node, String word, int depth) {
    if (node == null) {
        return [1];
    }
    if (depth == word.length()) {
        if (node.isWord) {
            node.isWord = false;
            return nodeHasNoChildren(node);
        }
        return false;
    }
    int index = word.charAt(depth) - 'a';
    boolean shouldDeleteCurrentNode = delete(node.children[[2]], word, depth + 1);
    if (shouldDeleteCurrentNode) {
        node.children[[3]] = null;
        return !node.isWord && nodeHasNoChildren(node);
    }
    return false;
}

private boolean nodeHasNoChildren(TrieNode node) {
    for (TrieNode child : node.children) {
        if (child != null) {
            return false;
        }
    }
    return true;
}

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

Afalse

Btrue

Cindex

Ddepth

Attempts:

3 left

💡 Hint

Common Mistakes

Returning true when node is null, causing incorrect deletion.

Using depth instead of index to access children.

Not setting the child to null after deletion.

Return false if node is null. Use index to access children for recursive delete and null assignment.

Practice

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

easy

A. To perform arithmetic operations on words

B. To sort words alphabetically

C. To store words in a linked list

D. To efficiently store and search words by their prefixes

Solution

1. Step 1: Understand Trie structure

   A Trie stores characters of words in a tree-like structure where each node represents a character.

2. Step 2: Identify Trie usage in word search

   It allows quick prefix-based search, making it efficient to find words starting with given letters.

3. Final Answer:

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

4. Quick Check:

   Trie = prefix search [OK]

Hint: Trie is all about prefix-based fast word search [OK]

Common Mistakes:

• Confusing Trie with sorting data structures
• Thinking Trie stores words as linked lists
• Assuming Trie performs arithmetic on words

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

easy

A. class TrieNode { char val; TrieNode[] children = new TrieNode[26]; boolean isWord; }

B. class TrieNode { int val; TrieNode children; boolean isWord; }

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

D. class TrieNode { char val; List<TrieNode> children; boolean isWord; }

Solution

1. Step 1: Check data types for Trie node

   Each node stores a character, an array of 26 children for letters a-z, and a boolean to mark word end.

2. Step 2: Validate options

   class TrieNode { char val; TrieNode[] children = new TrieNode[26]; boolean isWord; } matches this structure exactly with char val, TrieNode[] children of size 26, and boolean isWord.

3. Final Answer:

   class TrieNode { char val; TrieNode[] children = new TrieNode[26]; boolean isWord; } -> Option A

4. Quick Check:

   Correct TrieNode declaration = class TrieNode { char val; TrieNode[] children = new TrieNode[26]; boolean isWord; } [OK]

Hint: Trie nodes use char + array of 26 children + boolean flag [OK]

Common Mistakes:

• Using int or String instead of char for node value
• Using single child instead of array for children
• Using List instead of fixed-size array for children

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

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

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

medium

A. false
false

B. true
false

C. true
true

D. false
true

Solution

1. Step 1: Insert words "cat" and "car" into Trie

   Both words are inserted character by character, marking the last node's isWord as true.

2. Step 2: Search for "cat" and "cap"

   "cat" exists with isWord true, so search returns true. "cap" path is missing 'p' node, so returns false.

3. Final Answer:

   true false -> Option B

4. Quick Check:

   Inserted words found = true, missing word = false [OK]

Hint: Search returns true only if full word path and isWord true [OK]

Common Mistakes:

• Assuming partial prefix returns true
• Not marking isWord correctly on insert
• Confusing character indexing in children array

4. Identify the bug in the following Trie search method and choose the correct fix:

boolean search(String word) {
  TrieNode node = root;
  for (int i = 0; i <= word.length(); i++) {
    int idx = word.charAt(i) - 'a';
    if (node.children[idx] == null) return false;
    node = node.children[idx];
  }
  return node.isWord;
}

medium

A. Initialize idx before loop

B. Return true inside the loop

C. Change loop condition to i < word.length()

D. Remove return statement inside loop

Solution

1. Step 1: Analyze loop boundary

   The loop runs from i = 0 to i <= word.length(), which causes index out of bounds at last iteration.

2. Step 2: Fix loop condition

   Changing condition to i < word.length() prevents accessing invalid index and correctly iterates over characters.

3. Final Answer:

   Change loop condition to i < word.length() -> Option C

4. Quick Check:

   Loop boundary fix prevents index error [OK]

Hint: Loop over string chars with i < length, not <= length [OK]

Common Mistakes:

• Using <= instead of < in loop condition
• Trying to fix by moving idx initialization
• Removing return inside loop causing wrong logic

5. Given a 2D board of characters and a list of words, which approach best uses a Trie to efficiently find all words present on the board? A sample board:

[
  ['o','a','a','n'],
  ['e','t','a','e'],
  ['i','h','k','r'],
  ['i','f','l','v']
]

Words: ["oath", "pea", "eat", "rain"]

hard

A. Build a Trie from words, then DFS on board checking prefixes in Trie

B. Check each word by scanning entire board without Trie

C. Use a hash set for words and scan board rows only

D. Sort words and board rows, then binary search each word

Solution

1. Step 1: Build Trie from given words

   Insert all words into a Trie to enable prefix checking during search.

2. Step 2: Perform DFS on board cells

   From each cell, explore neighbors recursively, checking if current path matches any prefix in Trie to prune search.

3. Step 3: Collect words found when Trie node marks word end

   This approach efficiently finds all words without redundant searches.

4. Final Answer:

   Build a Trie from words, then DFS on board checking prefixes in Trie -> Option A

5. Quick Check:

   Trie + DFS = efficient word search on board [OK]

Hint: Use Trie for prefix pruning during DFS on board [OK]

Common Mistakes:

• Searching words one by one scanning whole board
• Ignoring prefix pruning causing slow search
• Using sorting and binary search which doesn't fit 2D board