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How to Solve Maximum Good Subtree Score Problem
Master the Maximum Good Subtree Score LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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LeetCode ProblemMaximum Good Subtree Score
You are given an undirected tree rooted at node 0 with n nodes numbered from 0 to n - 1. Each node i has an integer value vals[i], and its parent is given by par[i]. A subset of nodes within the subtree of a node is called good if every digit from 0 to 9 appears at most once in the decimal representation of the values of the selected nodes. The score of a good subset is the sum of the values of its nodes. Define an array maxScore of length n, where maxScore[u] represents the maximum possible sum of values of a good subset of nodes that belong to the subtree rooted at node u, including u itself and all its descendants. Return the sum of all values in maxScore. Since the answer may be large, return it modulo 109 + 7.
ArrayDynamic ProgrammingBit ManipulationTreeDepth-First SearchBitmask
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Problem Breakdown
Understanding the Maximum Good Subtree Score Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
You are given an undirected tree rooted at node 0 with n nodes numbered from 0 to n - 1. Each node i has an integer value vals[i], and its parent is given by par[i]. A subset of nodes within the subtree of a node is called good if every digit from 0 to 9 appears at most once in the decimal representation of the values of the selected nodes. The score of a good subset is the sum of the values of its nodes. Define an array maxScore of length n, where maxScore[u] represents the maximum possible sum of values of a good subset of nodes that belong to the subtree rooted at node u, including u itself and all its descendants. Return the sum of all values in maxScore. Since the answer may be large, return it modulo 109 + 7.
HardProblem #3575
LeetCodeMaximum Good Subtree Score
Related Topics
ArrayDynamic ProgrammingBit ManipulationTreeDepth-First SearchBitmask
How Phantom Code Helps
Get real-time assistance for Maximum Good Subtree Score problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
vals = [2,3], par = [-1,0]
Output
8
# Example 2
Input
vals = [1,5,2], par = [-1,0,0]
Output
15
# Example 3
Input
vals = [34,1,2], par = [-1,0,1]
Output
42
# Example 4
Input
vals = [3,22,5], par = [-1,0,1]
Output
18
Constraints
1 <= n == vals.length <= 500
1 <= vals[i] <= 109
par.length == n
par[0] == -1
0 <= par[i] < n for i in [1, n - 1]
The input is generated such that the parent array par represents a valid tree.
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Solve Maximum Good Subtree Score — You are given an undirected tree rooted at node 0 with n nodes numbered from 0 t...
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 Maximum Good Subtree Score and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Maximum Good Subtree Score 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 Good Subtree Score?
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 Good Subtree Score?
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 Good Subtree Score 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 Good Subtree Score 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 Good Subtree Score 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 Good Subtree Score 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 Good Subtree Score 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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