What is the time complexity of Total Distance Traveled?

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

What data structures are used to solve Total Distance Traveled?

This problem uses Math, Simulation. Understanding these concepts is essential for solving this Easy problem efficiently.

What are the key insights for solving Total Distance Traveled?

The problem involves simulating the fuel consumption and transfer process step-by-step. A `while` loop is appropriate to iterate until the main tank is empty.

Which companies ask LeetCode 2739. Total Distance Traveled in interviews?

This problem is frequently asked at Compass.

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Total Distance Traveled - LeetCode 2739 Solution

Total Distance Traveled - Complete Solution Guide

Total Distance Traveled is LeetCode problem 2739, a Easy level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3, java, cpp, c.

Problem Statement

A truck has two fuel tanks. You are given two integers, mainTank representing the fuel present in the main tank in liters and additionalTank representing the fuel present in the additional tank in liters. The truck has a mileage of 10 km per liter. Whenever 5 liters of fuel get used up in the main tank, if the additional tank has at least 1 liters of fuel, 1 liters of fuel will be transferred from the additional tank to the main tank. Return the maximum distance which can be traveled. Note: Inje

Detailed Explanation

The problem describes a truck with two fuel tanks: a main tank and an additional tank. The truck consumes fuel at a rate of 1 liter per 10 km. Every time 5 liters are consumed from the main tank, 1 liter is transferred from the additional tank to the main tank, if available. The goal is to determine the maximum distance the truck can travel given the initial fuel levels in both tanks.

Solution Approach

The provided solution uses a `while` loop that continues as long as there is fuel in the main tank. Inside the loop, it checks if there's enough fuel in both tanks to perform a transfer (main tank >= 5 and additional tank >= 1). If so, it simulates the 50km travel (5 liters consumed, 1 liter transferred), updates the fuel levels, and adds 50 to the total distance. Otherwise, it calculates the remaining distance based on the fuel in the main tank and exits the loop.

Step-by-Step Algorithm

Initialize `distance` to 0.
Enter a `while` loop that continues as long as `mainTank` is greater than 0.
Check if `mainTank` >= 5 and `additionalTank` >= 1. If true, perform a fuel transfer: add 50 to `distance`, subtract 5 from `mainTank`, add 1 to `mainTank`, and subtract 1 from `additionalTank`.
If the condition in step 3 is false (not enough fuel for transfer), calculate the remaining distance (`mainTank * 10`), add it to `distance`, and set `mainTank` to 0 to end the loop.
Return `distance`.

Key Insights

The problem involves simulating the fuel consumption and transfer process step-by-step.
A `while` loop is appropriate to iterate until the main tank is empty.
Careful handling of the conditional fuel transfer is crucial to avoid incorrect calculations.

Complexity Analysis

Time Complexity: O(m)

Space Complexity: O(1)

Topics

This problem involves: Math, Simulation.

Companies

Asked at: Compass.

Total Distance Traveled | LeetCode 2739

Easy

Math Simulation

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

Solution Code

Available in:

class Solution {
    public int distanceTraveled(int mainTank, int additionalTank) {
        int distance = 0;
        while (mainTank > 0) {
            if (mainTank >= 5 && additionalTank >= 1) {
                distance += 50;
                mainTank -= 5;
                mainTank += 1;
                additionalTank -= 1;
            } else {
                distance += mainTank * 10;
                mainTank = 0;
            }
        }
        return distance;
    }
}

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Problem Info

Description

Problem 2739: Total Distance Traveled - Detailed explanation and solution approaches.

Topics

Math Simulation

Companies

Compass

Stats

Difficulty:Easy

Languages:4

Companies:1

Problem #:2739

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
Initialize `distance` to 0.
2
Enter a `while` loop that continues as long as `mainTank` is greater than 0.
3
Check if `mainTank` >= 5 and `additionalTank` >= 1. If true, perform a fuel transfer: add 50 to `distance`, subtract 5 from `mainTank`, add 1 to `mainTank`, and subtract 1 from `additionalTank`.
4
If the condition in step 3 is false (not enough fuel for transfer), calculate the remaining distance (`mainTank * 10`), add it to `distance`, and set `mainTank` to 0 to end the loop.
5
Return `distance`.

💡

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(m)

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The time complexity is determined by the number of iterations of the `while` loop. In the worst case, the loop runs until the main tank is empty or the additional tank is empty, which depends on the minimum of the two initial fuel levels. The space complexity is constant because only a few integer variables are used, regardless of the input size.

📖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

Iterative approach with fuel consumption tracking

Instead of checking for 5-liter intervals, one could directly iterate through fuel consumption liter by liter, handling transfer logic when the mainTank hits multiples of 5.

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

Trade-offs: This approach might be slightly less efficient due to the higher number of iterations but could offer more granularity if future problem extensions involve more complex fuel consumption scenarios.

✨

Key Insights

1The problem involves simulating the fuel consumption and transfer process step-by-step.
2A `while` loop is appropriate to iterate until the main tank is empty.
3Careful handling of the conditional fuel transfer is crucial to avoid incorrect calculations.

📚

Key Terms Explained

For Students

Edge Cases

Edge case 1: `mainTank` is less than 5 initially. The solution correctly handles this by directly calculating the distance and setting `mainTank` to 0.
Edge case 2: `additionalTank` is 0 initially. The solution correctly proceeds without any transfer, using only the fuel in the main tank.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Forgetting to update the fuel levels in both tanks after each fuel transfer or consumption.

✗Common mistake 2: Incorrectly handling the conditional logic for fuel transfer—missing one of the conditions (`mainTank >= 5` or `additionalTank >= 1`).

✗Common mistake 3: Off-by-one errors when calculating the distance based on fuel consumption.

✅

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: Simulating fuel consumption and management in vehicles with auxiliary fuel tanks, optimizing fuel efficiency.

🏦Real-world scenario 2: Modeling resource management scenarios where a primary resource is replenished from a secondary resource when a threshold is reached (e.g., water storage in a drought).

💡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

Even for easy problems, discuss time and space complexity. Interviewers want to see you think analytically.

⚠️ 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: July 10, 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

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

@AlgoMasterJun 30

❓

Frequently Asked Questions

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 "Total Distance Traveled"?

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

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