What is the time complexity of Ant on the Boundary?

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

What data structures are used to solve Ant on the Boundary?

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

What are the key insights for solving Ant on the Boundary?

Insight 1: The problem can be solved by tracking the ant's current position. The key is to realize that returning to the boundary simply means the ant's position becomes 0 again. Insight 2: A simple iterative approach, traversing the array and updating the position is sufficient. No complex data structures are needed.

Which companies ask LeetCode 3028. Ant on the Boundary in interviews?

This problem is frequently asked at Accenture.

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Ant on the Boundary - LeetCode 3028 Solution

Ant on the Boundary - Complete Solution Guide

Ant on the Boundary is LeetCode problem 3028, 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

An ant is on a boundary. It sometimes goes left and sometimes right . You are given an array of non-zero integers nums . The ant starts reading nums from the first element of it to its end. At each step, it moves according to the value of the current element: If nums[i] < 0 , it moves left by -nums[i] units. If nums[i] > 0 , it moves right by nums[i] units. Return the number of times the ant returns to the boundary. Notes: There is an infinite space on both sides of the boundary. We check whethe

Detailed Explanation

The problem describes an ant moving along a boundary. The ant's movement is dictated by an array of integers, `nums`. Positive numbers indicate a rightward movement by that amount, and negative numbers indicate a leftward movement. The ant starts at the boundary (position 0). The goal is to determine how many times the ant returns to the boundary during its journey across the number array. The ant only checks its position relative to the boundary after completing each move, not during the move itself.

Solution Approach

The provided solution uses a simple iterative approach. It initializes the ant's position (`pos` or `position`) to 0 and a counter (`count`) to 0. The algorithm iterates through the `nums` array. In each iteration, it updates the ant's position by adding the current number from the array. After each update, it checks if the ant's position is 0. If it is, the `count` is incremented. Finally, the function returns the `count`, representing the number of times the ant returned to the boundary.

Step-by-Step Algorithm

Step 1: Initialize the ant's position (`pos`) to 0 and the return count (`count`) to 0.
Step 2: Iterate through the input array `nums`.
Step 3: For each number `num` in `nums`, add `num` to `pos` (update the ant's position).
Step 4: Check if `pos` is equal to 0. If it is, increment `count`.
Step 5: After iterating through the entire array, return `count`.

Key Insights

Insight 1: The problem can be solved by tracking the ant's current position. The key is to realize that returning to the boundary simply means the ant's position becomes 0 again.
Insight 2: A simple iterative approach, traversing the array and updating the position is sufficient. No complex data structures are needed.
Insight 3: The problem's constraint that numbers are non-zero simplifies the solution. We don't need to handle 0 values specially.

Complexity Analysis

Time Complexity: O(n)

Space Complexity: O(1)

Topics

This problem involves: Array, Simulation, Prefix Sum.

Companies

Asked at: Accenture.

Ant on the Boundary | LeetCode 3028

Easy

Array Simulation Prefix Sum

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

Solution Code

Available in:

class Solution {
    public int returnToBoundaryCount(int[] nums) {
        int position = 0;
        int count = 0;
        for (int num : nums) {
            position += num;
            if (position == 0) {
                count++;
            }
        }
        return count;
    }
}

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Problem Info

Description

Problem 3028: Ant on the Boundary - Detailed explanation and solution approaches.

Topics

Array Simulation Prefix Sum

Companies

Accenture

Stats

Difficulty:Easy

Languages:4

Companies:1

Problem #:3028

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 the ant's position (`pos`) to 0 and the return count (`count`) to 0.
2
Step 2: Iterate through the input array `nums`.
3
Step 3: For each number `num` in `nums`, add `num` to `pos` (update the ant's position).
4
Step 4: Check if `pos` is equal to 0. If it is, increment `count`.
5
Step 5: After iterating through the entire array, return `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)

👍 Linear - Good! Visits each element once.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The algorithm iterates through the input array `nums` once. The number of iterations is directly proportional to the size of the array (n). The space used is constant because only a few variables (`pos`, `count`) 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

✨

Key Insights

1Insight 1: The problem can be solved by tracking the ant's current position. The key is to realize that returning to the boundary simply means the ant's position becomes 0 again.
2Insight 2: A simple iterative approach, traversing the array and updating the position is sufficient. No complex data structures are needed.
3Insight 3: The problem's constraint that numbers are non-zero simplifies the solution. We don't need to handle 0 values specially.

📚

Key Terms Explained

For Students

Array

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

Edge Cases

Edge case 1: An empty input array (`nums` is empty). The solution correctly handles this by returning 0 because the ant never moves.
Edge case 2: The ant only moves to the right and then left, returning to zero multiple times. The algorithm correctly counts each return to 0.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Forgetting to check for the return to the boundary after each step. This would result in incorrect counting.

✗Common mistake 2: Incorrectly handling negative numbers. Misinterpreting how negative numbers affect the position can lead to wrong results.

✅

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 a simple robotic system moving along a linear track, where positive and negative values represent movement directions. The algorithm can be used to determine how many times the robot returns to its starting point.

🏦Real-world scenario 2: Tracking financial gains and losses. Positive numbers represent profits, and negative numbers represent losses. The algorithm could be adapted to count how many times the net profit/loss returns to zero.

💡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.

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 27, 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

❓

Frequently Asked Questions

What is the most efficient way to solve array problems?

Most array problems can be solved efficiently using techniques like two-pointer approach, sliding window, or hash maps. The key is identifying whether the array is sorted (enabling binary search) or if tracking seen elements (using hash maps) can help achieve O(n) time complexity.

How should I approach easy-level algorithm problems?

Easy problems build foundational skills. Focus on: 1) Understanding the problem completely before coding, 2) Writing clean, readable code, 3) Handling all edge cases (empty input, single element, etc.), 4) Analyzing time and space complexity. Don't skip complexity analysis even for simple solutions.

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 "Ant on the Boundary"?

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 simulation techniques can optimize the solution. Always handle edge cases and validate your approach with examples before coding.

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