Prefix Search Using Trie in DSA Javascript - Build from Scratch

Prefix Search Using Trie

📖 Scenario: Imagine you have a list of words and want to quickly find all words that start with a certain prefix, like searching names in your phone contacts.

🎯 Goal: You will build a simple Trie data structure to store words and then search for all words starting with a given prefix.

📋 What You'll Learn

Create a TrieNode class with a children object and a boolean isEndOfWord

Create a Trie class with insert(word) and startsWith(prefix) methods

Insert given words into the trie

Search and return all words starting with the given prefix

Print the list of words found by prefix search

💡 Why This Matters

🌍 Real World

Tries are used in search engines, autocomplete features, and spell checkers to quickly find words starting with certain letters.

💼 Career

Understanding Tries helps in roles involving search optimization, text processing, and building efficient data retrieval systems.

1

Create TrieNode and Trie classes

Create a class called TrieNode with a constructor that initializes children as an empty object and isEndOfWord as false. Then create a class called Trie with a constructor that initializes root as a new TrieNode.

DSA Javascript

// Your code here

Hint

Think of TrieNode as a box holding letters and a flag if a word ends there. Trie starts with an empty root node.

2

Add insert method to Trie

Add a method called insert(word) to the Trie class. It should start from this.root and for each character in word, create a new TrieNode in children if it does not exist. After the last character, set isEndOfWord to true.

DSA Javascript

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

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

    // Your code here
}

Hint

Walk through each letter of the word, add nodes if missing, and mark the end of the word.

3

Add startsWith method to find words by prefix

Add a method called startsWith(prefix) to the Trie class. It should find the node matching the last character of prefix. Then collect all words starting from that node by traversing children recursively. Return the list of words with the prefix included.

DSA Javascript

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

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

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

    // Add startsWith method below
}

Hint

First find the node for the prefix, then explore all child nodes to collect full words.

4

Insert words and print prefix search results

Create a Trie instance called trie. Insert these words exactly: 'apple', 'app', 'apricot', 'banana'. Then print the result of trie.startsWith('ap').

DSA Javascript

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

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

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

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

        const words = [];

        function dfs(currentNode, path) {
            if (currentNode.isEndOfWord) {
                words.push(path);
            }
            for (let childChar in currentNode.children) {
                dfs(currentNode.children[childChar], path + childChar);
            }
        }

        dfs(node, prefix);
        return words;
    }
}

// Your code here

Hint

Insert the words exactly, then print the list of words starting with 'ap'. The output should be an array of matching words.

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