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Maven Clinic·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Went through a coding screen for a Software Engineer role at Maven Clinic. Just the one algorithmic problem, nothing too wild, but it's the kind of question where you either see the pattern or you don't.

Questions Asked (1)

Q1

Given an array of meeting time intervals, determine whether a person can attend all of them without any two overlapping.

Algorithms & Data Structures
Author's notes

Knew I needed to sort first but for a second I was second-guessing whether to sort by start or end time.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem: intervals are inclusive/exclusive, and overlapping means any shared time. Then propose sorting intervals by start time and checking for overlaps between consecutive intervals, which is efficient and easy to implement.

Pro tip: Mention that sorting by start time is optimal because it allows a single pass to detect overlaps, and discuss edge cases like zero-length intervals or back-to-back meetings to show thoroughness.

1. Clarify the problem

Ask if intervals are inclusive of endpoints and whether back-to-back meetings count as overlapping. Confirm input format and constraints.

2. Choose an approach

Propose sorting intervals by start time, then iterate through them to check if the current interval's start is before the previous interval's end.

3. Walk through an example

Use a small example to demonstrate the algorithm, showing how sorting and comparison detect overlaps.

4. Analyze complexity

State that sorting takes O(n log n) time and the subsequent check is O(n), resulting in O(n log n) overall, with O(1) extra space if sorting in place.

5. Handle edge cases

Discuss cases like empty input, single interval, zero-length intervals, and intervals that touch at endpoints.

Key Points to Mention

  • Sorting intervals by start time
  • Checking overlap condition: current.start < previous.end
  • Time complexity: O(n log n) due to sorting
  • Space complexity: O(1) if sorting in place, O(n) if creating a new sorted list
  • Edge cases: empty array, single interval, zero-length intervals
  • Alternative approaches like sweep line or priority queue, but sorting is optimal

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