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How to Solve Minimum Cost Path with Alternating Directions II Problem
Master the Minimum Cost Path with Alternating Directions II LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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Start Free for WindowsMedium#3603
LeetCode ProblemMinimum Cost Path with Alternating Directions II
You are given two integers m and n representing the number of rows and columns of a grid, respectively. The cost to enter cell (i, j) is defined as (i + 1) * (j + 1). You are also given a 2D integer array waitCost where waitCost[i][j] defines the cost to wait on that cell. The path will always begin by entering cell (0, 0) on move 1 and paying the entrance cost. At each step, you follow an alternating pattern: Return the minimum total cost required to reach (m - 1, n - 1).
ArrayDynamic ProgrammingMatrix
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Problem Breakdown
Understanding the Minimum Cost Path with Alternating Directions II Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
You are given two integers m and n representing the number of rows and columns of a grid, respectively. The cost to enter cell (i, j) is defined as (i + 1) * (j + 1). You are also given a 2D integer array waitCost where waitCost[i][j] defines the cost to wait on that cell. The path will always begin by entering cell (0, 0) on move 1 and paying the entrance cost. At each step, you follow an alternating pattern: Return the minimum total cost required to reach (m - 1, n - 1).
MediumProblem #3603
LeetCodeMinimum Cost Path with Alternating Directions II
Related Topics
ArrayDynamic ProgrammingMatrix
How Phantom Code Helps
Get real-time assistance for Minimum Cost Path with Alternating Directions II problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
m = 1, n = 2, waitCost = [[1,2]]
Output
3
# Example 2
Input
m = 2, n = 2, waitCost = [[3,5],[2,4]]
Output
9
# Example 3
Input
m = 2, n = 3, waitCost = [[6,1,4],[3,2,5]]
Output
16
Constraints
1 <= m, n <= 105
2 <= m * n <= 105
waitCost.length == m
waitCost[0].length == n
0 <= waitCost[i][j] <= 105
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Solve Minimum Cost Path with Alternating Directions II — You are given two integers m and n representing the number of rows and columns o...
Here's the optimal approach using Array:
def solve(input):
# Optimal O(n) solution
return result
Time: O(n) | Space: O(n)
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Frequently Asked Questions
Common questions about solving Minimum Cost Path with Alternating Directions II and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Minimum Cost Path with Alternating Directions II during interviews?
Phantom Code generates complete solutions instantly with proper complexity analysis, letting you focus on explaining your approach and demonstrating problem-solving skills rather than getting stuck on implementation details during high-pressure situations.
What if the interviewer asks follow-up questions or modifications to problems like Minimum Cost Path with Alternating Directions II?
Phantom Code adapts in real-time. Screenshot the modified problem or use audio mode to capture the interviewer's follow-up, and get an updated solution within seconds — including edge cases and optimizations.
Can Phantom Code help me communicate my solution for problems like Minimum Cost Path with Alternating Directions II?
Yes. Phantom Code provides step-by-step approach explanations with 3 progressive thoughts, so you can walk through your solution naturally. It also provides time and space complexity analysis to discuss trade-offs.
How does Phantom Code assist with different programming languages for Minimum Cost Path with Alternating Directions II type problems?
Phantom Code supports 11 programming languages including Python, Java, C++, JavaScript, TypeScript, Go, Rust, Ruby, Swift, Kotlin, and C#. Set your preferred language and get idiomatic solutions.
What coding mistakes does Phantom Code help me avoid during Minimum Cost Path with Alternating Directions II interviews?
Phantom Code catches common mistakes like off-by-one errors, missing edge cases, incorrect base conditions, and suboptimal approaches. It provides clean, well-structured code that handles all edge cases.
Is Phantom Code detectable when solving problems like Minimum Cost Path with Alternating Directions II during live interviews?
No. Phantom Code runs as an invisible desktop overlay that doesn't appear in screen shares, recordings, or proctoring software. It works with Zoom, HackerRank, CodeSignal, CoderPad, and all major platforms.
How does Phantom Code help when I'm struggling with Minimum Cost Path with Alternating Directions II style questions under pressure?
The AI provides structured guidance: first the approach (what algorithm/data structure to use and why), then the implementation with clean code, and finally complexity analysis. This helps you think clearly even under pressure.
Does Phantom Code work for the coding platforms used in Minimum Cost Path with Alternating Directions II interviews?
Yes. Phantom Code works with all major coding platforms including LeetCode, HackerRank, CodeSignal, CoderPad, HackerEarth, and any browser-based coding environment.
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