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Sliding Window Average After Dropping the Largest Values

Last updated: Jul 18, 2026

Quick Overview

Compute one average per fixed-size sliding window after removing exactly the largest k values, counting duplicates separately. Support negative numbers, k equal to zero, and a stream-like pass over up to 200,000 inputs without re-sorting every window.

  • medium
  • Google
  • Coding & Algorithms
  • Software Engineer

Sliding Window Average After Dropping the Largest Values

Company: Google

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: medium

Interview Round: Technical Screen

Quick Answer: Compute one average per fixed-size sliding window after removing exactly the largest k values, counting duplicates separately. Support negative numbers, k equal to zero, and a stream-like pass over up to 200,000 inputs without re-sorting every window.

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|Home/Coding & Algorithms/Google

Sliding Window Average After Dropping the Largest Values

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May 23, 2026, 12:00 AM
mediumSoftware EngineerTechnical ScreenCoding & Algorithms
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