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

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Prefix Search Result

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

DSA Javascript

class TrieNode {
  constructor() {
    this.children = {};
    this.isEnd = false;
  }
}

class Trie {
  constructor() {
    this.root = new TrieNode();
  }

  insert(word) {
    let node = this.root;
    for (const char of word) {
      if (!node.children[char]) {
        node.children[char] = new TrieNode();
      }
      node = node.children[char];
    }
    node.isEnd = true;
  }

  startsWith(prefix) {
    let node = this.root;
    for (const char of prefix) {
      if (!node.children[char]) {
        return [];
      }
      node = node.children[char];
    }
    const results = [];
    const dfs = (currNode, path) => {
      if (currNode.isEnd) results.push(path);
      for (const c in currNode.children) {
        dfs(currNode.children[c], path + c);
      }
    };
    dfs(node, prefix);
    return results;
  }
}

const trie = new Trie();
['apple', 'app', 'application', 'bat', 'ball'].forEach(w => trie.insert(w));
console.log(trie.startsWith('app'));

A ["app", "apple", "application"]

B ["apple", "application"]

C ["app", "application"]

D ["bat", "ball"]

💡 Hint

Think about all words starting exactly with 'app' including the prefix itself.

The Trie stores all words. The startsWith method finds all words starting with 'app'. The words 'app', 'apple', and 'application' start with 'app'.

🧠 Conceptual

intermediate

Number of Nodes in Trie After Insertions

After inserting the words ['cat', 'car', 'cart', 'dog'] into an empty Trie, how many nodes does the Trie contain?

A 8

B 10

C 7

D 9

💡 Hint

Count shared prefixes only once.

The words share prefixes: 'ca' is shared by 'cat', 'car', 'cart'. Counting nodes: root + c + a + t + r + t + d + o + g = 9 nodes.

🔧 Debug

advanced

Identify the Error in Trie Search Method

What error does the following Trie search method produce when searching for a prefix that does not exist?

DSA Javascript

startsWith(prefix) {
  let node = this.root;
  for (const char of prefix) {
    node = node.children[char];
  }
  return node !== undefined;
}

A SyntaxError due to missing return statement

B Returns false correctly

C TypeError: Cannot read property 'children' of undefined

D Always returns true

💡 Hint

What happens if node.children[char] is undefined and you try to access its children?

If prefix character is missing, node.children[char] is undefined. Next loop tries to access children of undefined causing TypeError.

🚀 Application

advanced

Find All Words with Prefix in Trie

Given a Trie with words inserted, which method correctly returns all words starting with a given prefix?

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

B Return all words in Trie and filter those starting with prefix

C Check only if prefix is a word in Trie and return it

D Return empty list if prefix length is less than 3

💡 Hint

Think about efficient search using Trie structure.

The efficient way is to find the node representing prefix, then explore all descendants to get words starting with prefix.

❓ Predict Output

expert

Output of Complex Trie Prefix Search

What is the output of the following code snippet?

DSA Javascript

class TrieNode {
  constructor() {
    this.children = {};
    this.isEnd = false;
  }
}

class Trie {
  constructor() {
    this.root = new TrieNode();
  }

  insert(word) {
    let node = this.root;
    for (const char of word) {
      if (!node.children[char]) {
        node.children[char] = new TrieNode();
      }
      node = node.children[char];
    }
    node.isEnd = true;
  }

  startsWith(prefix) {
    let node = this.root;
    for (const char of prefix) {
      if (!node.children[char]) return [];
      node = node.children[char];
    }
    const results = [];
    const dfs = (currNode, path) => {
      if (currNode.isEnd) results.push(path);
      for (const c in currNode.children) {
        dfs(currNode.children[c], path + c);
      }
    };
    dfs(node, prefix);
    return results;
  }
}

const trie = new Trie();
['team', 'teach', 'test', 'tester', 'testing'].forEach(w => trie.insert(w));
console.log(trie.startsWith('te'));

A ["tester", "testing"]

B ["team", "teach", "test", "tester", "testing"]

C ["team", "teach"]

D ["test", "tester", "testing"]

💡 Hint

All words starting with 'te' should be included.

All inserted words start with 'te', so all are returned in lexicographical order of DFS traversal.

Practice

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

easy

A. To efficiently find all words starting with a given prefix

B. To sort words alphabetically

C. To store numbers in ascending order

D. To perform arithmetic operations quickly

Solution

1. Step 1: Understand Trie usage

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

2. Step 2: Identify prefix search benefit

   This structure allows quick traversal to find all words sharing a prefix without scanning all words.

3. Final Answer:

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

4. Quick Check:

   Trie = prefix search efficiency [OK]

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

Common Mistakes:

• Confusing Trie with sorting algorithms
• Thinking Trie stores numbers only
• Assuming Trie is for arithmetic

2. Which of the following is the correct way to initialize an empty Trie node in JavaScript?

easy

A. const node = [];

B. const node = new Map();

C. const node = null;

D. const node = { children: {}, isEnd: false };

Solution

1. Step 1: Understand Trie node structure

   A Trie node typically has a children object to hold next characters and a boolean to mark word end.

2. Step 2: Match correct initialization

   const node = { children: {}, isEnd: false }; correctly creates an object with children as empty object and isEnd as false.

3. Final Answer:

   const node = { children: {}, isEnd: false }; -> Option D

4. Quick Check:

   Trie node = object with children and isEnd [OK]

Hint: Trie nodes use objects with children and end flag [OK]

Common Mistakes:

• Using array instead of object for children
• Setting node to null instead of object
• Using Map without isEnd flag

3. What will be the output of the following code snippet?

class TrieNode {
  constructor() {
    this.children = {};
    this.isEnd = false;
  }
}

class Trie {
  constructor() {
    this.root = new TrieNode();
  }
  insert(word) {
    let node = this.root;
    for (const char of word) {
      if (!node.children[char]) {
        node.children[char] = new TrieNode();
      }
      node = node.children[char];
    }
    node.isEnd = true;
  }
  startsWith(prefix) {
    let node = this.root;
    for (const char of prefix) {
      if (!node.children[char]) return false;
      node = node.children[char];
    }
    return true;
  }
}

const trie = new Trie();
trie.insert('cat');
trie.insert('car');
trie.insert('dog');
console.log(trie.startsWith('ca'));

medium

A. true

B. false

C. undefined

D. Error

Solution

1. Step 1: Insert words into Trie

   Words 'cat', 'car', and 'dog' are inserted, creating nodes for each character.

2. Step 2: Check prefix 'ca'

   Both 'cat' and 'car' start with 'ca', so traversal finds nodes for 'c' and 'a'.

3. Final Answer:

   true -> Option A

4. Quick Check:

   Prefix 'ca' exists = true [OK]

Hint: If prefix matches inserted words, startsWith returns true [OK]

Common Mistakes:

• Confusing startsWith with exact word search
• Expecting false if prefix is partial
• Ignoring that multiple words share prefix

4. Identify the bug in the following Trie insert method and select the fix:

insert(word) {
  let node = this.root;
  for (const char of word) {
    if (node.children[char]) {
      node.children[char] = new TrieNode();
    }
    node = node.children[char];
  }
  node.isEnd = true;
}

medium

A. Remove node.isEnd assignment

B. Change if condition to check if child does NOT exist before creating new node

C. Initialize node as null before loop

D. Use a Map instead of object for children

Solution

1. Step 1: Analyze insert method logic

   The code creates a new node only if node.children[char] exists, which is incorrect.

2. Step 2: Correct condition for node creation

   We should create a new node only if node.children[char] does NOT exist to avoid overwriting existing nodes.

3. Final Answer:

   Change if condition to check if child does NOT exist before creating new node -> Option B

4. Quick Check:

   Insert new node only if missing [OK]

Hint: Create new child node only if it does not exist [OK]

Common Mistakes:

• Creating new node when child already exists
• Forgetting to mark end of word
• Initializing node incorrectly

5. Given a list of words ['apple', 'app', 'apricot', 'banana'], how would you use a Trie to find all words starting with 'ap'? Choose the correct approach.

hard

A. Insert only words starting with 'ap' into Trie and ignore others

B. Sort the list and filter words starting with 'ap' using string methods

C. Insert all words into Trie, then traverse nodes for prefix 'ap' and collect all descendant words

D. Use a hash map to store words and check prefix by substring matching

Solution

1. Step 1: Build Trie with all words

   Insert all words so the Trie contains complete data for prefix search.

2. Step 2: Traverse Trie for prefix 'ap'

   Navigate nodes for 'a' then 'p', then collect all words from this subtree.

3. Step 3: Collect descendant words

   Gather words like 'apple', 'app', and 'apricot' that share the prefix.

4. Final Answer:

   Insert all words into Trie, then traverse nodes for prefix 'ap' and collect all descendant words -> Option C

5. Quick Check:

   Trie + prefix traversal = all matching words [OK]

Hint: Insert all words, then traverse prefix subtree to find matches [OK]

Common Mistakes:

• Filtering list without Trie defeats purpose
• Ignoring words not starting with prefix during insertion
• Using hash map instead of Trie for prefix search