What is the time complexity of Furthest Point From Origin?

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

What data structures are used to solve Furthest Point From Origin?

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

What are the key insights for solving Furthest Point From Origin?

Insight 1: The underscores can be strategically used to maximize the distance from the origin by assigning them to either 'L' or 'R' based on which direction leads to a further distance. Insight 2: Counting the number of 'L', 'R', and '_' characters is sufficient to determine the maximum distance. We don't need to simulate each possible move sequence explicitly.

Which companies ask LeetCode 2833. Furthest Point From Origin in interviews?

This problem is frequently asked at Barclays.

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Furthest Point From Origin - LeetCode 2833 Solution

Furthest Point From Origin - Complete Solution Guide

Furthest Point From Origin is LeetCode problem 2833, 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

You are given a string moves of length n consisting only of characters 'L' , 'R' , and '_' . The string represents your movement on a number line starting from the origin 0 . In the i th move, you can choose one of the following directions: move to the left if moves[i] = 'L' or moves[i] = '_' move to the right if moves[i] = 'R' or moves[i] = '_' Return the distance from the origin of the furthest point you can get to after n moves . Example 1: Input: moves = "L_RL__R" Output: 3 Explanation: The

Detailed Explanation

The problem asks you to determine the furthest distance from the origin (0) that can be reached after a series of movements on a number line. The movements are represented by a string where 'L' means move left, 'R' means move right, and '_' means you can choose either left or right. The goal is to find the maximum absolute distance from the origin that can be achieved by strategically choosing the direction for '_' moves.

Solution Approach

The solution iterates through the input string to count the occurrences of 'L', 'R', and '_'. It then calculates the maximum possible distance by strategically allocating the '_' moves. If 'R' count is greater than 'L' count, all the '_' moves are used to increase the right movements; otherwise they are used to increase left movements. The absolute difference between the adjusted 'R' and 'L' counts gives the maximum distance.

Step-by-Step Algorithm

Step 1: Initialize counters for 'L', 'R', and '_' characters to 0.
Step 2: Iterate through the input string `moves`. Increment the corresponding counter for each character encountered.
Step 3: Calculate the maximum possible distance: If the number of 'R's is greater than or equal to the number of 'L's, the furthest distance is (number of 'R's + number of '_'s) - (number of 'L's). Otherwise, it's (number of 'L's + number of '_'s) - (number of 'R's).
Step 4: Return the absolute value of the calculated distance.

Key Insights

Insight 1: The underscores can be strategically used to maximize the distance from the origin by assigning them to either 'L' or 'R' based on which direction leads to a further distance.
Insight 2: Counting the number of 'L', 'R', and '_' characters is sufficient to determine the maximum distance. We don't need to simulate each possible move sequence explicitly.
Insight 3: The maximum distance is achieved by aligning as many '_' moves as possible with the direction that has fewer 'L' or 'R' moves. This will balance out the positive and negative movements.

Complexity Analysis

Time Complexity: O(n)

Space Complexity: O(1)

Topics

This problem involves: String, Counting.

Companies

Asked at: Barclays.

Furthest Point From Origin | LeetCode 2833

Easy

String Counting

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

Solution Code

Available in:

class Solution {
    public int furthestDistanceFromOrigin(String moves) {
        int left = 0;
        int right = 0;
        int underscore = 0;
        for (char c : moves.toCharArray()) {
            if (c == 'L') {
                left++;
            } else if (c == 'R') {
                right++;
            } else {
                underscore++;
            }
        }
        return Math.abs(right - left) + underscore;
    }
}

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Problem Info

Description

Problem 2833: Furthest Point From Origin - Detailed explanation and solution approaches.

Topics

String Counting

Companies

Barclays

Stats

Difficulty:Easy

Languages:4

Companies:1

Problem #:2833

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

4 steps

1
Step 1: Initialize counters for 'L', 'R', and '_' characters to 0.
2
Step 2: Iterate through the input string `moves`. Increment the corresponding counter for each character encountered.
3
Step 3: Calculate the maximum possible distance: If the number of 'R's is greater than or equal to the number of 'L's, the furthest distance is (number of 'R's + number of '_'s) - (number of 'L's). Otherwise, it's (number of 'L's + number of '_'s) - (number of 'R's).
4
Step 4: Return the absolute value of the calculated 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(n)

👍 Linear - Good! Visits each element once.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The time complexity is O(n) because the code iterates through the input string of length n once. The space complexity is O(1) because it uses a constant amount of extra space to store the counters for 'L', 'R', and '_', 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

Simulating all possible move sequences

This approach would generate all possible move sequences by recursively exploring choices for '_' characters and track the maximum distance.

Time: O(2^m)Space: O(m)

Trade-offs: This approach is exponentially slower and uses more space than the optimal approach presented. It's less efficient but provides a more brute-force understanding of the problem.

✨

Key Insights

1Insight 1: The underscores can be strategically used to maximize the distance from the origin by assigning them to either 'L' or 'R' based on which direction leads to a further distance.
2Insight 2: Counting the number of 'L', 'R', and '_' characters is sufficient to determine the maximum distance. We don't need to simulate each possible move sequence explicitly.
3Insight 3: The maximum distance is achieved by aligning as many '_' moves as possible with the direction that has fewer 'L' or 'R' moves. This will balance out the positive and negative movements.

📚

Key Terms Explained

For Students

String

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

Edge Cases

Edge case 1: An empty string. The solution correctly handles this by returning 0.
Edge case 2: A string with only '_' characters. The solution correctly calculates the maximum distance as the number of underscores.
Edge case 3: A string with equal numbers of 'L' and 'R' characters. The maximum distance will simply be the number of underscores

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Incorrectly handling the underscores. Simply adding the underscore count to either the left or right count without considering the balance between 'L' and 'R' will lead to an incorrect answer.

✗Common mistake 2: Forgetting to take the absolute value of the final distance. The furthest distance can be either positive or negative, depending on the net movement.

✅

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: Modeling a robot's movement along a line where certain actions are uncertain (represented by '_'). This helps determine the robot's maximum possible reach.

🏦Real-world scenario 2: Analyzing stock market fluctuations where some future movements are uncertain. This approach can help to estimate the maximum possible profit or loss.

💡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

String problems often involve sliding windows or two pointers. Consider if the character set is limited (lowercase letters = only 26 possibilities).

🎯 Interview Tip

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

⚠️ Watch Out

Mutating strings directly in languages where strings are immutable. Use StringBuilder or arrays.

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: October 12, 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

Try solving this without using extra space first. It's a great exercise for understanding the underlying pattern.

@CodeNinjaJul 14

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

@TechLeadJul 7

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

@DevExpert92Jun 30

❓

Frequently Asked Questions

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 "Furthest Point From Origin"?

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

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