What is the time complexity of The Number of Full Rounds You Have Played?

The optimal solution has a time complexity of O(1).

What data structures are used to solve The Number of Full Rounds You Have Played?

This problem uses Math, String. Understanding these concepts is essential for solving this Medium problem efficiently.

What are the key insights for solving The Number of Full Rounds You Have Played?

Insight 1: Convert login and logout times into minutes to simplify calculations. Insight 2: Handle the case where the logout time is earlier than the login time, indicating play across midnight, by adding 24 hours (1440 minutes) to the logout time.

Which companies ask LeetCode 1904. The Number of Full Rounds You Have Played in interviews?

This problem is frequently asked at General Motors.

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The Number of Full Rounds You Have Played - LeetCode 1904 Solution

The Number of Full Rounds You Have Played - Complete Solution Guide

The Number of Full Rounds You Have Played is LeetCode problem 1904, a Medium level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3, java, cpp, c.

Problem Statement

You are participating in an online chess tournament. There is a chess round that starts every 15 minutes. The first round of the day starts at 00:00 , and after every 15 minutes, a new round starts. For example, the second round starts at 00:15 , the fourth round starts at 00:45 , and the seventh round starts at 01:30 . You are given two strings loginTime and logoutTime where: loginTime is the time you will login to the game, and logoutTime is the time you will logout from the game. If logoutTim

Detailed Explanation

The problem asks us to calculate the number of complete 15-minute chess rounds a player participated in, given their login and logout times. A chess round starts every 15 minutes, beginning at 00:00. If the logout time is earlier than the login time, it implies the player played across midnight. The inputs are two strings, `loginTime` and `logoutTime`, in the format 'hh:mm'. The output is an integer representing the number of full rounds played.

Solution Approach

The solution converts the given login and logout times into total minutes from the start of the day (00:00). It then addresses the scenario where the game spans across midnight by adding 24 hours worth of minutes to the logout time if it is earlier than the login time. Next, it calculates the number of full rounds that can be played, considering the login and logout times. This is done by finding the first possible complete 15-minute round *after* the login time, and the last completed round *before* the logout time. The difference between these represents the number of full rounds played.

Step-by-Step Algorithm

Step 1: Parse the `loginTime` and `logoutTime` strings to extract the hours and minutes as integers.
Step 2: Convert the login and logout times to minutes from the start of the day (00:00).
Step 3: If the `logout_minutes` is less than `login_minutes`, add 24 * 60 (1440) to `logout_minutes` to account for playing across midnight.
Step 4: Calculate the `start_quarter`. This is the index of the first possible full round the player could participate in. Add 14 to login_minutes and integer divide by 15 to find this quarter. The addition ensures we find the next *complete* round after the login.
Step 5: Calculate the `end_quarter`. This is the index of the last completed full round the player participated in. Integer divide logout_minutes by 15 to find the last completed quarter.
Step 6: Calculate the number of full rounds played by subtracting `start_quarter` from `end_quarter`.
Step 7: Return the number of full rounds played, ensuring the result is not negative (using `max(0, num_rounds)`).

Key Insights

Insight 1: Convert login and logout times into minutes to simplify calculations.
Insight 2: Handle the case where the logout time is earlier than the login time, indicating play across midnight, by adding 24 hours (1440 minutes) to the logout time.
Insight 3: Determine the starting and ending 'quarters' (15-minute intervals) based on login and logout times and calculate the difference.

Complexity Analysis

Time Complexity: O(1)

Space Complexity: O(1)

Topics

This problem involves: Math, String.

Companies

Asked at: General Motors.

The Number of Full Rounds You Have Played | LeetCode 1904

Medium

Math String

Time: O(1)Space: O(1)

Solution Code

Available in:

class Solution {
    public int numberOfRounds(String loginTime, String logoutTime) {
        int login_h = Integer.parseInt(loginTime.substring(0, 2));
        int login_m = Integer.parseInt(loginTime.substring(3, 5));
        int logout_h = Integer.parseInt(logoutTime.substring(0, 2));
        int logout_m = Integer.parseInt(logoutTime.substring(3, 5));

        int login_minutes = login_h * 60 + login_m;
        int logout_minutes = logout_h * 60 + logout_m;

        if (logout_minutes < login_minutes) {
            logout_minutes += 24 * 60;
        }

        int start_quarter = (login_minutes + 14) / 15;
        
        int end_quarter = logout_minutes / 15;
        
        int num_rounds = end_quarter - start_quarter;
        
        return Math.max(0, num_rounds);
    }
}

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Problem Info

Description

Problem 1904: The Number of Full Rounds You Have Played - Detailed explanation and solution approaches.

Topics

Math String

Companies

General Motors

Stats

Difficulty:Medium

Languages:4

Companies:1

Problem #:1904

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

7 steps

1
Step 1: Parse the `loginTime` and `logoutTime` strings to extract the hours and minutes as integers.
2
Step 2: Convert the login and logout times to minutes from the start of the day (00:00).
3
Step 3: If the `logout_minutes` is less than `login_minutes`, add 24 * 60 (1440) to `logout_minutes` to account for playing across midnight.
4
Step 4: Calculate the `start_quarter`. This is the index of the first possible full round the player could participate in. Add 14 to login_minutes and integer divide by 15 to find this quarter. The addition ensures we find the next *complete* round after the login.
5
Step 5: Calculate the `end_quarter`. This is the index of the last completed full round the player participated in. Integer divide logout_minutes by 15 to find the last completed quarter.
6
Step 6: Calculate the number of full rounds played by subtracting `start_quarter` from `end_quarter`.
7
Step 7: Return the number of full rounds played, ensuring the result is not negative (using `max(0, num_rounds)`).

💡

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(1)

⚡ Constant time - Super fast! Same speed regardless of input size.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The code performs a fixed number of arithmetic operations regardless of the input values. There are no loops or recursive calls whose execution depends on the size of the input. Therefore, the time complexity is constant, O(1). Similarly, the code uses a fixed number of variables to store the extracted hours, minutes, and calculated values. The space used does not depend on the input size, so the space complexity is also constant, O(1).

📖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 datetime objects (Python)

In Python, you could use the `datetime` module to represent the times and calculate the difference. This approach can make the code more readable but may not improve the time complexity in this specific case.

Time: O(1)Space: O(1)

Trade-offs: This approach might be more readable, but involves more overhead in creating and manipulating datetime objects compared to simple integer arithmetic. For this particular problem, the arithmetic approach is likely faster and more efficient.

✨

Key Insights

1Insight 1: Convert login and logout times into minutes to simplify calculations.
2Insight 2: Handle the case where the logout time is earlier than the login time, indicating play across midnight, by adding 24 hours (1440 minutes) to the logout time.
3Insight 3: Determine the starting and ending 'quarters' (15-minute intervals) based on login and logout times and calculate the difference.

📚

Key Terms Explained

For Students

String

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

Edge Cases

Edge case 1: `loginTime` and `logoutTime` are within the same 15-minute interval, resulting in zero full rounds. The solution correctly calculates `start_quarter` and `end_quarter` to be the same, leading to a result of 0.
Edge case 2: `logoutTime` is earlier than `loginTime`, indicating play across midnight. The solution handles this by adding 24 hours to the `logout_minutes`, ensuring correct calculation of full rounds.
Edge case 3: loginTime and logoutTime being very close to a 15 minute boundary, still correctly computes the number of rounds

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Not handling the case where `logoutTime` is earlier than `loginTime` correctly, leading to incorrect calculations when the game spans across midnight.

✗Common mistake 2: Incorrectly calculating the starting and ending quarters by not properly adjusting the `login_minutes` and `logout_minutes` to account for full rounds only.

✗Common mistake 3: Assuming that the difference between the minutes directly translates to number of rounds without converting to quarters.

✅

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: Calculating billable hours in 15-minute increments for consultants or freelancers.

🏦Real-world scenario 2: Tracking usage of a shared resource (e.g., a meeting room, a piece of equipment) in 15-minute slots to determine availability and billing.

💡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

Consider multiple approaches before coding. Mentioning alternatives shows breadth of knowledge.

⚠️ Watch Out

Always test your solution with edge cases: empty input, single element, and boundary values.

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: September 13, 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

In a real interview, always clarify constraints first. Ask about input size and value ranges.

@TechLeadJul 14

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

@DevExpert92Jul 7

❓

Frequently Asked Questions

How do I handle string manipulation efficiently?

In languages with immutable strings (Java, Python, C#), use StringBuilder/list to avoid O(n) concatenation cost. Consider using character arrays for in-place modifications. For pattern matching, consider KMP or Rabin-Karp for O(n+m) complexity.

What techniques are commonly tested in medium-difficulty problems?

Medium problems often require combining multiple techniques: two-pointer with hash maps, BFS/DFS with state tracking, dynamic programming with optimization, or divide-and-conquer approaches. They test your ability to recognize patterns and choose the right combination of techniques.

How should I practice algorithm problems effectively?

Focus on understanding patterns rather than memorizing solutions. After solving a problem, review optimal solutions and understand the intuition. Group similar problems to recognize patterns. Practice explaining your approach out loud. Review problems after a few days to test retention.

What is the optimal approach for "The Number of Full Rounds You Have Played"?

For this medium-level Math 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.

🤖 Need help with this problem?