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How to Solve Maximum Score After Applying Operations on a Tree Problem
Master the Maximum Score After Applying Operations on a Tree LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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Start Free for WindowsMedium#2925
LeetCode ProblemMaximum Score After Applying Operations on a Tree
There is an undirected tree with n nodes labeled from 0 to n - 1, and rooted at node 0. You are given a 2D integer array edges of length n - 1, where edges[i] = [ai, bi] indicates that there is an edge between nodes ai and bi in the tree. You are also given a 0-indexed integer array values of length n, where values[i] is the value associated with the ith node. You start with a score of 0. In one operation, you can: A tree is healthy if the sum of values on the path from the root to any leaf node is different than zero. Return the maximum score you can obtain after performing these operations on the tree any number of times so that it remains healthy.
Dynamic ProgrammingTreeDepth-First Search
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Problem Breakdown
Understanding the Maximum Score After Applying Operations on a Tree Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
There is an undirected tree with n nodes labeled from 0 to n - 1, and rooted at node 0. You are given a 2D integer array edges of length n - 1, where edges[i] = [ai, bi] indicates that there is an edge between nodes ai and bi in the tree. You are also given a 0-indexed integer array values of length n, where values[i] is the value associated with the ith node. You start with a score of 0. In one operation, you can: A tree is healthy if the sum of values on the path from the root to any leaf node is different than zero. Return the maximum score you can obtain after performing these operations on the tree any number of times so that it remains healthy.
MediumProblem #2925
LeetCodeMaximum Score After Applying Operations on a Tree
Related Topics
Dynamic ProgrammingTreeDepth-First Search
How Phantom Code Helps
Get real-time assistance for Maximum Score After Applying Operations on a Tree problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
edges = [[0,1],[0,2],[0,3],[2,4],[4,5]], values = [5,2,5,2,1,1]
Output
11
# Example 2
Input
edges = [[0,1],[0,2],[1,3],[1,4],[2,5],[2,6]], values = [20,10,9,7,4,3,5]
Output
40
Constraints
2 <= n <= 2 * 104
edges.length == n - 1
edges[i].length == 2
0 <= ai, bi < n
values.length == n
1 <= values[i] <= 109
The input is generated such that edges represents a valid tree.
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Solve Maximum Score After Applying Operations on a Tree — There is an undirected tree with n nodes labeled from 0 to n - 1, and rooted at ...
Here's the optimal approach using Dynamic Programming:
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 Maximum Score After Applying Operations on a Tree and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Maximum Score After Applying Operations on a Tree 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 Maximum Score After Applying Operations on a Tree?
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 Maximum Score After Applying Operations on a Tree?
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 Maximum Score After Applying Operations on a Tree 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 Maximum Score After Applying Operations on a Tree 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 Maximum Score After Applying Operations on a Tree 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 Maximum Score After Applying Operations on a Tree 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 Maximum Score After Applying Operations on a Tree 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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