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Google·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Google frontend engineer interview, got asked a classic CS fundamentals question. Nothing too wild but it's Google so you know they want you to be precise about it.

Questions Asked (1)

Q1

Can you explain how binary search works?

Algorithms & Data Structures
Author's notes

Felt like a warmup but I still fumbled the off-by-one explanation.

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AI HintsAI Generated

Suggested Approach

Start by defining binary search as an efficient algorithm for finding a target in a sorted array by repeatedly halving the search interval. Then walk through the step-by-step process, emphasizing the role of the midpoint and the conditions for adjusting the low and high pointers. Finally, discuss time and space complexity, and mention edge cases like empty arrays or duplicates.

Pro tip: At Google, interviewers value clarity and correctness: explicitly state the loop invariant (e.g., target is within [low, high]) and discuss potential pitfalls like integer overflow when computing mid, showing you think about robust code.

1. Define the problem and preconditions

State that binary search requires a sorted array and a target value, and it returns the index of the target or -1 if not found.

2. Explain the algorithm step-by-step

Describe initializing low and high pointers, then iteratively computing the midpoint and comparing it to the target, adjusting low or high accordingly until the target is found or the search space is empty.

3. Analyze complexity

Mention that time complexity is O(log n) because the search space halves each iteration, and space complexity is O(1) for the iterative version.

4. Discuss edge cases and variations

Cover scenarios like empty array, target not present, duplicates (which may require finding first/last occurrence), and the importance of avoiding integer overflow when calculating mid.

Key Points to Mention

  • Requires sorted input
  • Time complexity O(log n)
  • Space complexity O(1) for iterative, O(log n) for recursive
  • Mid calculation: mid = low + (high - low) / 2 to avoid overflow
  • Loop invariant: target is within [low, high] if present
  • Handling duplicates: may need to find leftmost or rightmost occurrence

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