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How to Solve Maximum Genetic Difference Query Problem
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LeetCode ProblemMaximum Genetic Difference Query
There is a rooted tree consisting of n nodes numbered 0 to n - 1. Each node's number denotes its unique genetic value (i.e. the genetic value of node x is x). The genetic difference between two genetic values is defined as the bitwise-XOR of their values. You are given the integer array parents, where parents[i] is the parent for node i. If node x is the root of the tree, then parents[x] == -1. You are also given the array queries where queries[i] = [nodei, vali]. For each query i, find the maximum genetic difference between vali and pi, where pi is the genetic value of any node that is on the path between nodei and the root (including nodei and the root). More formally, you want to maximize vali XOR pi. Return an array ans where ans[i] is the answer to the ith query.
ArrayHash TableBit ManipulationDepth-First SearchTrie
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Problem Breakdown
Understanding the Maximum Genetic Difference Query Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
There is a rooted tree consisting of n nodes numbered 0 to n - 1. Each node's number denotes its unique genetic value (i.e. the genetic value of node x is x). The genetic difference between two genetic values is defined as the bitwise-XOR of their values. You are given the integer array parents, where parents[i] is the parent for node i. If node x is the root of the tree, then parents[x] == -1. You are also given the array queries where queries[i] = [nodei, vali]. For each query i, find the maximum genetic difference between vali and pi, where pi is the genetic value of any node that is on the path between nodei and the root (including nodei and the root). More formally, you want to maximize vali XOR pi. Return an array ans where ans[i] is the answer to the ith query.
HardProblem #1938
LeetCodeMaximum Genetic Difference Query
Related Topics
ArrayHash TableBit ManipulationDepth-First SearchTrie
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Examples
# Example 1
Input
parents = [-1,0,1,1], queries = [[0,2],[3,2],[2,5]]
Output
[2,3,7]
# Example 2
Input
parents = [3,7,-1,2,0,7,0,2], queries = [[4,6],[1,15],[0,5]]
Output
[6,14,7]
Constraints
2 <= parents.length <= 105
0 <= parents[i] <= parents.length - 1 for every node i that is not the root.
parents[root] == -1
1 <= queries.length <= 3 * 104
0 <= nodei <= parents.length - 1
0 <= vali <= 2 * 105
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Solve Maximum Genetic Difference Query — There is a rooted tree consisting of n nodes numbered 0 to n - 1. Each node's nu...
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Frequently Asked Questions
Common questions about solving Maximum Genetic Difference Query and using Phantom Code AI during coding interviews.
How does Phantom Code AI help me solve coding problems like Maximum Genetic Difference Query during interviews?
Phantom Code AI 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.
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What coding mistakes does Phantom Code AI help me avoid during Maximum Genetic Difference Query interviews?
Phantom Code AI 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.
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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.
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