Bytedance·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

First round for an SRE role at Bytedance. Pretty light technically, binary search on a sorted array, and there was enough time left over to just talk about the company with the interviewer.

Questions Asked (1)

Given a sorted array, find a target element using binary search.

Algorithms & Data Structures

Author's notes

Not a LeetCode problem apparently, which I appreciated.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., array size, duplicates, target presence) and then explain the binary search algorithm step-by-step. Emphasize the invariant that the target lies within the current search range, and discuss time and space complexity.

Pro tip: Mention that binary search can be implemented iteratively or recursively, but iterative is preferred for constant space. Also, highlight common pitfalls like integer overflow when calculating mid and off-by-one errors in loop conditions.

1. Clarify requirements and edge cases

Ask about array size, whether duplicates exist, if the target is guaranteed to be present, and if the array is sorted in ascending order. Discuss edge cases like empty array or single element.

2. Explain the algorithm

Describe how binary search works: maintain low and high pointers, compute mid, compare with target, and adjust pointers accordingly. Emphasize the loop condition and termination.

3. Walk through an example

Choose a small sorted array and demonstrate the steps, showing how the search range halves each time. This helps validate the approach and catch off-by-one errors.

4. Analyze complexity

State that time complexity is O(log n) and space complexity is O(1) for iterative implementation. Mention that recursive uses O(log n) space due to call stack.

5. Discuss variations and optimizations

Mention variations like finding first/last occurrence, or using binary search on answer. Also, note how to avoid integer overflow by using mid = low + (high - low) / 2.

Key Points to Mention

Time complexity O(log n) and space complexity O(1) for iterative.
Importance of sorted array precondition.
Handling duplicates: binary search can find any occurrence, but modifications needed for first/last.
Avoiding integer overflow in mid calculation.
Loop condition: while (low <= high) and updating low = mid + 1 or high = mid - 1.
Return value: index of target or -1 if not found.

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