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Uber·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jul 2026

Summary

Uber SWE coding round, got a classic math problem that feels easy until you actually think about the constraints. No built-in sqrt allowed, so you have to actually know what you're doing.

Questions Asked (1)

Q1

Given a non-negative integer x, return the integer square root of x rounded down, without using any built-in exponent or square root functions.

Algorithms & Data Structures
Author's notes

My first instinct was to just loop from 0 upward and check when i*i exceeds x.

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AI HintsAI Generated

Suggested Approach

Use binary search to find the largest integer whose square is less than or equal to x, handling edge cases like x=0 and x=1. Avoid overflow by comparing mid to x/mid instead of mid*mid, and clearly explain the time and space complexity.

Pro tip: Mention that you can use Newton's method for a faster convergence, but binary search is simpler and more reliable for interviews. Also, explicitly handle integer overflow to show attention to detail.

1. Clarify and handle edge cases

Confirm that x is non-negative and discuss edge cases: x=0 returns 0, x=1 returns 1. Also consider large values that might cause overflow.

2. Choose binary search approach

Explain that binary search on the range [0, x] is efficient because the square root function is monotonic. Set low=0, high=x, and iterate while low <= high.

3. Implement safe comparison

Compute mid = low + (high - low) // 2. To avoid overflow, compare mid with x // mid instead of computing mid*mid. Adjust low or high based on the comparison.

4. Return the result

When the loop ends, high will be the integer square root rounded down. Return high.

5. Analyze complexity

State that time complexity is O(log x) and space complexity is O(1). Optionally, mention alternative approaches like Newton's method.

Key Points to Mention

  • Binary search on the answer space [0, x]
  • Overflow-safe comparison using division instead of multiplication
  • Edge cases: x=0, x=1, and large integers
  • Time complexity O(log x) and space complexity O(1)
  • Alternative: Newton's method for faster convergence
  • Handling of integer division and rounding down

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.