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How to Solve Queue Reconstruction by Height Problem
Master the Queue Reconstruction by Height LeetCode problem with undetectable real-time assistance. Get instant solutions and explanations during your coding interviews.
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Start Free for WindowsMedium#406
LeetCode ProblemQueue Reconstruction by Height
You are given an array of people, people, which are the attributes of some people in a queue (not necessarily in order). Each people[i] = [hi, ki] represents the ith person of height hi with exactly ki other people in front who have a height greater than or equal to hi. Reconstruct and return the queue that is represented by the input array people. The returned queue should be formatted as an array queue, where queue[j] = [hj, kj] is the attributes of the jth person in the queue (queue[0] is the person at the front of the queue).
ArrayBinary Indexed TreeSegment TreeSorting
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Problem Breakdown
Understanding the Queue Reconstruction by Height Problem
Let's break down this LeetCode problem and understand what makes it challenging in interview settings.
Problem Statement
You are given an array of people, people, which are the attributes of some people in a queue (not necessarily in order). Each people[i] = [hi, ki] represents the ith person of height hi with exactly ki other people in front who have a height greater than or equal to hi. Reconstruct and return the queue that is represented by the input array people. The returned queue should be formatted as an array queue, where queue[j] = [hj, kj] is the attributes of the jth person in the queue (queue[0] is the person at the front of the queue).
MediumProblem #406
LeetCodeQueue Reconstruction by Height
Related Topics
ArrayBinary Indexed TreeSegment TreeSorting
How Phantom Code Helps
Get real-time assistance for Queue Reconstruction by Height problems during coding interviews. Phantom Code provides instant solutions and explanations.
Examples
# Example 1
Input
people = [[7,0],[4,4],[7,1],[5,0],[6,1],[5,2]]
Output
[[5,0],[7,0],[5,2],[6,1],[4,4],[7,1]]
# Example 2
Input
people = [[6,0],[5,0],[4,0],[3,2],[2,2],[1,4]]
Output
[[4,0],[5,0],[2,2],[3,2],[1,4],[6,0]]
Constraints
1 <= people.length <= 2000
0 <= hi <= 106
0 <= ki < people.length
It is guaranteed that the queue can be reconstructed.
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Solve Queue Reconstruction by Height — You are given an array of people, people, which are the attributes of some peopl...
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def solve(input):
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Frequently Asked Questions
Common questions about solving Queue Reconstruction by Height and using Phantom Code during coding interviews.
How does Phantom Code help me solve coding problems like Queue Reconstruction by Height 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 Queue Reconstruction by Height?
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 Queue Reconstruction by Height?
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 Queue Reconstruction by Height 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 Queue Reconstruction by Height 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 Queue Reconstruction by Height 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 Queue Reconstruction by Height 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 Queue Reconstruction by Height 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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