Why Count Words with Given Prefix in DSA Typescript?

The Big Idea

What if you could find all words starting with a few letters instantly, no matter how big your list is?

The Scenario

Imagine you have a huge list of words, like a dictionary, and you want to find out how many words start with a certain set of letters, like "pre".

Doing this by checking each word one by one is like looking for all red apples in a giant basket by picking each apple up and checking its color.

The Problem

Checking every word manually takes a lot of time, especially if the list is very long.

It's easy to make mistakes or miss some words when doing this by hand or with simple loops.

This slow and error-prone method makes it hard to get quick answers.

The Solution

Using a special structure called a Trie, we can organize words so that all words with the same prefix share the same path.

This lets us quickly jump to the part where the prefix ends and count all words that start with it without checking each word individually.

Before vs After

✗ Before

let count = 0;
for (let word of words) {
  if (word.startsWith(prefix)) {
    count++;
  }
}

✓ After

class TrieNode {
  children = new Map<string, TrieNode>();
  count = 0;
}

// Insert words and count prefix matches efficiently

What It Enables

This lets us instantly find how many words start with any prefix, even in huge word lists, making searches fast and reliable.

Real Life Example

Search engines use this to suggest words or phrases as you type, by quickly counting how many words start with the letters you entered.

Key Takeaways

Manual checking is slow and error-prone for large word lists.

Tries organize words by prefixes to speed up counting.

Counting words with a prefix becomes fast and easy.

Practice

1. What does the function countWordsStartingWith(words: string[], prefix: string): number do in the context of counting words with a given prefix?

easy

A. Counts the total number of characters in all words

B. Counts how many words contain the prefix anywhere inside

C. Counts how many words in the list start with the given prefix

D. Returns the longest word starting with the prefix

Solution

1. Step 1: Understand the function purpose

   The function is designed to count words that begin with a specific prefix, not just contain it anywhere.

2. Step 2: Compare options with function goal

   Only Counts how many words in the list start with the given prefix matches the goal of counting words starting exactly with the prefix.

3. Final Answer:

   Counts how many words in the list start with the given prefix -> Option C

4. Quick Check:

   Counting words starting with prefix = Counts how many words in the list start with the given prefix [OK]

Hint: Look for words starting exactly with prefix, not containing it [OK]

Common Mistakes:

• Confusing 'start with' and 'contain' prefix
• Thinking it returns words instead of count
• Assuming it counts characters, not words

2. Which of the following TypeScript code snippets correctly counts words starting with a prefix pre in an array words?

easy

A. words.filter(word => word.startsWith(pre)).length

B. words.map(word => word.startsWith(pre)).length

C. words.reduce((count, word) => count + word.includes(pre), 0)

D. words.forEach(word => word.startsWith(pre))

Solution

1. Step 1: Identify correct method to filter words

   The filter method returns an array of words starting with the prefix, then length counts them.

2. Step 2: Check other options for correctness

   words.map(word => word.startsWith(pre)).length returns an array of booleans, so length is total words, not count of matches. words.reduce((count, word) => count + word.includes(pre), 0) uses includes incorrectly and sums booleans without conversion. words.forEach(word => word.startsWith(pre)) does not return a count.

3. Final Answer:

   words.filter(word => word.startsWith(pre)).length -> Option A

4. Quick Check:

   Filter + length counts matches = words.filter(word => word.startsWith(pre)).length [OK]

Hint: Use filter with startsWith, then get length [OK]

Common Mistakes:

• Using map instead of filter for counting
• Using includes instead of startsWith
• Using forEach without counting

3. What is the output of the following TypeScript code?

const words = ['apple', 'app', 'application', 'banana', 'apply'];
const prefix = 'app';
const count = words.filter(word => word.startsWith(prefix)).length;
console.log(count);

medium

A. 3

B. 4

C. 5

D. 2

Solution

1. Step 1: Identify words starting with 'app'

   Words starting with 'app' are 'apple', 'app', 'application', and 'apply' (4 words).

2. Step 2: Count these words

   Counting them gives 4.

3. Final Answer:

   4 -> Option B

4. Quick Check:

   Words starting with 'app' = 4 [OK]

Hint: Count words starting exactly with prefix 'app' [OK]

Common Mistakes:

• Counting 'banana' mistakenly
• Counting only exact 'app' word
• Confusing includes with startsWith

4. The following TypeScript code is intended to count words starting with prefix pre, but it returns 0. What is the error?

const words = ['prefix', 'preach', 'prevent', 'post'];
const pre = 'pre';
let count = 0;
for (let i = 0; i < words.length; i++) {
  if (words[i].startWith(pre)) {
    count++;
  }
}
console.log(count);

medium

A. Method name should be startsWith, not startWith

B. Variable pre is not defined

C. Loop should start from 1, not 0

D. count should be initialized to 1

Solution

1. Step 1: Check method name correctness

   The method to check prefix is startsWith, but code uses startWith, which is undefined.

2. Step 2: Understand effect of typo

   Because of the typo, condition is always false, so count remains 0.

3. Final Answer:

   Method name should be startsWith, not startWith -> Option A

4. Quick Check:

   Correct method name fixes count [OK]

Hint: Check method spelling: startsWith, not startWith [OK]

Common Mistakes:

• Using startWith instead of startsWith
• Incorrect loop index start
• Wrong count initialization

5. Given a large list of words, which data structure would optimize counting how many words start with a given prefix efficiently for multiple queries?

hard

A. Array sorted alphabetically

B. Stack storing words

C. Hash Map with full words as keys

D. Trie (Prefix Tree)

Solution

1. Step 1: Understand prefix query optimization

   Trie stores words by characters in a tree, allowing fast prefix searches.

2. Step 2: Compare other data structures

   Sorted arrays require binary search but less efficient for many prefix queries. Hash maps store full words, not prefixes. Stacks do not support prefix queries efficiently.

3. Final Answer:

   Trie (Prefix Tree) -> Option D

4. Quick Check:

   Trie enables fast prefix counts [OK]

Hint: Use Trie for fast prefix counting in many queries [OK]

Common Mistakes:

• Choosing array or hash map for prefix queries
• Not knowing Trie supports prefix efficiently
• Confusing stack usage for prefix search