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The no-exponent constraint is what makes this more than a throwaway warmup.
Clarify constraints and edge cases, then propose a binary search on the range [0, x] to find the largest integer whose square is ≤ x. Discuss time and space complexity, and optionally mention Newton's method as an alternative.
Pro tip: Mention that binary search avoids overflow by using mid <= x / mid instead of mid * mid, and note that for large x, Newton's method converges faster.
Ask about input size, overflow concerns, and expected time complexity. Confirm that x is non-negative and that built-in exponent functions are prohibited.
Propose binary search as a simple O(log x) solution. Alternatively, mention Newton's method for faster convergence.
Set low=0, high=x. While low <= high, compute mid, and if mid <= x / mid, update result and low; else high = mid - 1. Return result.
State O(log x) time and O(1) space. Walk through edge cases like x=0, x=1, and perfect squares.
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