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LinkedIn·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026Remote

Summary

LinkedIn software engineer interview with a sliding window problem that looked easy until the follow-up made me rethink everything I'd written.

Questions Asked (1)

Q1

Given a binary array, you can flip at most one 0 to a 1. Return the length of the longest contiguous run of 1s you can achieve. Then: can you solve it in O(1) space if the array arrives as a stream, one element at a time?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The base problem I got pretty fast, sliding window with a counter tracking how many zeros are inside the window.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then present a sliding window solution that tracks the last zero position to compute the maximum run of 1s with at most one flip. For the streaming variant, explain how to maintain the same logic in O(1) space by keeping only the necessary state variables.

Pro tip: Emphasize that the streaming solution is essentially the same sliding window but without storing the array, and discuss how you would handle the flip count if it were generalized to k flips.

1. Clarify the problem

Confirm that the array contains only 0s and 1s, that you can flip at most one 0, and that you need the length of the longest contiguous run of 1s after the flip. Discuss edge cases like all 1s, all 0s, and empty array.

2. Outline the sliding window approach

Explain that you can use a sliding window that allows at most one zero. Maintain the window boundaries and the index of the last zero seen. When a second zero is encountered, move the left boundary to just after the previous zero.

3. Detail the algorithm with example

Walk through the algorithm step by step with a small example, showing how the window expands and contracts, and how the maximum length is updated. Highlight that the window always contains at most one zero.

4. Address the streaming variant

Explain that for a stream, you don't need to store the array; you only need to keep track of the current window length, the position of the last zero, and the maximum length seen so far. This uses O(1) space.

5. Analyze complexity and trade-offs

State that both solutions run in O(n) time and O(1) space. Mention that the streaming solution is more memory-efficient and suitable for large or infinite streams, but requires careful handling of state.

Key Points to Mention

  • Sliding window technique with at most one zero
  • Tracking the index of the last zero to efficiently move the left pointer
  • O(n) time complexity and O(1) space complexity
  • Streaming solution maintains only constant state: current window length, last zero index, max length
  • Edge cases: all 1s, all 0s, single element, empty array
  • Generalization to at most k flips (if asked)

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