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Find >n/3 elements in sorted array

Last updated: Mar 29, 2026

Quick Overview

This question evaluates understanding of algorithm design for sorted arrays, logarithmic-time search under constant-space constraints, frequency analysis for elements exceeding a threshold, and the ability to justify correctness and handle edge cases; it belongs to the Coding & Algorithms domain and emphasizes practical application with conceptual complexity analysis. It is commonly asked to assess proficiency in optimizing time and space complexity, reasoning about boundary conditions (e.g., small n or values near partition thresholds), and providing formal time/space analysis and correctness arguments.

  • Medium
  • TikTok
  • Coding & Algorithms
  • Software Engineer

Find >n/3 elements in sorted array

Company: TikTok

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: Medium

Interview Round: Technical Screen

Given a sorted array of integers nums of length n, return all values that occur more than floor(n/ 3) times. Design an algorithm that runs in O(log n) time and O( 1) extra space. Justify correctness, cover edge cases (e.g., n < 3, runs near boundaries), and provide time/space analysis.

Quick Answer: This question evaluates understanding of algorithm design for sorted arrays, logarithmic-time search under constant-space constraints, frequency analysis for elements exceeding a threshold, and the ability to justify correctness and handle edge cases; it belongs to the Coding & Algorithms domain and emphasizes practical application with conceptual complexity analysis. It is commonly asked to assess proficiency in optimizing time and space complexity, reasoning about boundary conditions (e.g., small n or values near partition thresholds), and providing formal time/space analysis and correctness arguments.

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TikTok
Sep 6, 2025, 12:00 AM
Software Engineer
Technical Screen
Coding & Algorithms
1
0

Given a sorted array of integers nums of length n, return all values that occur more than floor(n/ 3) times. Design an algorithm that runs in O(log n) time and O(

  1. extra space. Justify correctness, cover edge cases (e.g., n < 3, runs near boundaries), and provide time/space analysis.

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