What is the time complexity of Counting Words With a Given Prefix?

The optimal solution has a time complexity of O(n*m).

What data structures are used to solve Counting Words With a Given Prefix?

This problem uses Array, String, String Matching. Understanding these concepts is essential for solving this Easy problem efficiently.

What are the key insights for solving Counting Words With a Given Prefix?

Insight 1: The `startswith()` method in Python provides a concise way to check if a string begins with a given prefix. Insight 2: A simple iterative approach is sufficient to solve this problem due to the small input size constraints.

Which companies ask LeetCode 2185. Counting Words With a Given Prefix in interviews?

This problem is frequently asked at DoorDash.

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Counting Words With a Given Prefix - LeetCode 2185 Solution

Counting Words With a Given Prefix - Complete Solution Guide

Counting Words With a Given Prefix is LeetCode problem 2185, a Easy level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3.

Problem Statement

You are given an array of strings words and a string pref . Return the number of strings in words that contain pref as a prefix . A prefix of a string s is any leading contiguous substring of s . Example 1: Input: words = ["pay"," at tention","practice"," at tend"], pref = "at" Output: 2 Explanation: The 2 strings that contain "at" as a prefix are: " at tention" and " at tend". Example 2: Input: words = ["leetcode","win","loops","success"], pref = "code" Output: 0 Explanation: There are no strin

Detailed Explanation

The problem asks you to count how many strings in a given array `words` start with a specific prefix `pref`. The input is an array of strings (`words`) and a string (`pref`). The output is a single integer representing the number of strings in `words` that begin with `pref`. The constraints specify that the lengths of the words and the prefix are relatively small, limiting the scale of the problem. For example, if `words` = ["pay","attention","practice","attend"] and `pref` = "at", the output should be 2 because "attention" and "attend" start with "at".

Solution Approach

The solution uses a straightforward iterative approach. It iterates through each string in the `words` array. For each string, it uses the built-in `startswith()` method to check if the string begins with the given `pref`. If it does, a counter is incremented. Finally, the counter (representing the total number of strings with the prefix) is returned.

Step-by-Step Algorithm

Step 1: Initialize a counter variable `count` to 0.
Step 2: Iterate through each string `word` in the input array `words`.
Step 3: For each `word`, check if it starts with the prefix `pref` using `word.startswith(pref)`.
Step 4: If `word.startswith(pref)` is true, increment the `count`.
Step 5: After iterating through all words, return the final value of `count`.

Key Insights

Insight 1: The `startswith()` method in Python provides a concise way to check if a string begins with a given prefix.
Insight 2: A simple iterative approach is sufficient to solve this problem due to the small input size constraints.
Insight 3: No significant optimizations are needed given the constraints. More complex data structures or algorithms would introduce unnecessary overhead.

Complexity Analysis

Time Complexity: O(n*m)

Space Complexity: O(1)

Topics

This problem involves: Array, String, String Matching.

Companies

Asked at: DoorDash.

Counting Words With a Given Prefix | LeetCode 2185

Easy

Array String String Matching

Time: O(n*m)Space: O(1)

Solution Code

Available in:

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Problem Info

Description

Problem 2185: Counting Words With a Given Prefix - Detailed explanation and solution approaches.

Topics

Array String String Matching

Companies

DoorDash

Stats

Difficulty:Easy

Languages:2

Companies:1

Problem #:2185

Problem Explanation

💡

Think Before You Code

🤔 Ask Yourself

→What is the input? What output do I need?
→Can I solve a smaller version of this problem first?
→What patterns have I seen in similar problems?

✏️ Try This First

Before looking at the solution, try to solve it on paper with a simple example!

🚀 Try on LeetCode

Solution Approach

📋

Step-by-Step Solution

5 steps

1
Step 1: Initialize a counter variable `count` to 0.
2
Step 2: Iterate through each string `word` in the input array `words`.
3
Step 3: For each `word`, check if it starts with the prefix `pref` using `word.startswith(pref)`.
4
Step 4: If `word.startswith(pref)` is true, increment the `count`.
5
Step 5: After iterating through all words, return the final value of `count`.

💡

Pro Tip for Students

Try tracing through each step with a small example on paper before coding. Understanding "why" each step happens is more important than memorizing the code!

⚡

Complexity Analysis

⏱️

Time Complexity

O(n*m)

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The time complexity is O(n*m) because, in the worst case, the `startswith()` method might need to compare up to m characters for each of the n words. The space complexity is O(1) because the algorithm uses a constant amount of extra space regardless of the input size. The counter variable and loop variables take up constant space.

📖New to Big O? Click to learn more

Big O Notation - Quick Guide

O(1)Best - Instant

O(log n)Excellent - Binary Search

O(n)Good - One loop

O(n log n)OK - Sorting

O(n²)Slow - Nested loops

O(2ⁿ)Very Slow - Recursion

Alternative Approaches

Using list comprehension

A more concise solution can be achieved using Python's list comprehension feature.

Time: O(n*m)Space: O(n) - due to creating a new list

Trade-offs: List comprehension might be slightly faster in practice due to optimized Python implementation, but it consumes additional space to create a new list. The iterative approach is generally preferred for clarity and space efficiency in this case.

✨

Key Insights

1Insight 1: The `startswith()` method in Python provides a concise way to check if a string begins with a given prefix.
2Insight 2: A simple iterative approach is sufficient to solve this problem due to the small input size constraints.
3Insight 3: No significant optimizations are needed given the constraints. More complex data structures or algorithms would introduce unnecessary overhead.

📚

Key Terms Explained

For Students

Array

A collection of items stored at contiguous memory locations. Like a row of boxes.

String

A sequence of characters. Like a word or sentence in programming!

Edge Cases

Edge case 1: The prefix might be an empty string. The solution correctly handles this; `startswith('')` will return `True` for all strings.
Edge case 2: The input array `words` might be empty. The solution correctly handles this; it will return 0.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Incorrectly using `in` instead of `startswith()`. The `in` operator checks for substring presence anywhere in the string, not just at the beginning.

✗Common mistake 2: Forgetting to handle edge cases such as an empty input array or an empty prefix.

✅

Learning Tip

Every mistake is a learning opportunity! When you make an error, understand why it happened before moving on.

🌍

Where is This Used in Real Life?

💼Real-world scenario 1: Autocomplete suggestions in search engines or text editors. This algorithm can be used to quickly filter suggestions that match a user's prefix input.

🏦Real-world scenario 2: Network packet filtering. A router might filter network packets based on prefixes in their destination IP addresses.

💡Understanding real-world applications helps you see the "why" behind algorithms. It's not just about passing interviews—these concepts power the apps and websites you use every day!

Author's Notes

💡 Key Insight

When dealing with arrays, always consider if sorting would simplify the problem. Many array problems have O(n) solutions using hash maps or two-pointer technique.

🎯 Interview Tip

Use this problem to demonstrate clean code practices. Variable naming and code organization matter.

⚠️ Watch Out

Off-by-one errors are the most common mistake. Double-check your loop bounds and array indices.

👨‍💻 From Experience

This is one of the first problems I solved when learning Array. It's a great foundation for more complex problems.

Written by Saswata Mondal

Software Engineer • Algorithms Enthusiast • Interview Coach

👨‍💻

About the Author

👨‍💻

Saswata MondalAuthor400+ LC Problems

B.Tech CSE, IEM Kolkata | LeetCode Rating: 1672 (Top 15%)

Certified: IBM Java Developer, NPTEL Programming in Java

Last updated: June 26, 2024LeetCode Profile GitHub

This solution has been crafted based on my experience solving 400+ LeetCode problems. Each explanation is designed to help you understand the underlying concepts, not just memorize the code.

Community Tips & Insights

Don't forget to handle the edge case when the input is empty. Many candidates miss this in interviews.

@DevExpert92Jul 14

The key insight here is recognizing the pattern. Once you see it, the solution becomes straightforward.

@AlgoMasterJul 7

I was asked this exact problem at my Google interview. The interviewer wanted me to optimize space complexity.

@InterviewProJun 30

❓

Frequently Asked Questions

When should I use in-place modification vs creating a new array?

Use in-place modification when space complexity matters (O(1) space requirement) and the original array can be modified. Create a new array when you need to preserve the original data or when the problem involves significant restructuring that would complicate in-place logic.

What is the sliding window technique for string problems?

Sliding window maintains a "window" of characters with two pointers. Expand the right pointer to include characters, shrink from left when window violates constraints. Useful for substring problems, anagrams, and longest/shortest substring with properties.

What should I learn from easy problems?

Easy problems introduce core patterns that appear in harder problems. Master basic operations (iteration, conditionals, simple data structures), recognize common patterns (counting, searching, basic transformations), and practice explaining your thought process clearly.

What is the importance of time and space complexity analysis?

Complexity analysis is crucial because: 1) Interviewers always ask about it, 2) It helps you choose between approaches, 3) It demonstrates CS fundamentals. Always state both time and space complexity, and be prepared to explain how you derived them.

What is the optimal approach for "Counting Words With a Given Prefix"?

For this easy-level Array problem, the key is to identify the core pattern. Analyze the input constraints to determine acceptable time complexity. Consider whether string techniques can optimize the solution. Always handle edge cases and validate your approach with examples before coding.

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