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Liftoff·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Liftoff software engineer interview with a coding problem that looks deceptively simple but has a neat trick to it. Pretty standard technical screen vibe.

Questions Asked (1)

Q1

Given a list of positive integers representing daily cycling distances, compute the Eddington number: the largest integer E such that there are at least E days where the distance ridden was greater than or equal to E.

Algorithms & Data Structures
Author's notes

I'd never heard of the Eddington number before so I spent an embarrassing amount of time just re-reading the definition.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then propose an efficient algorithm such as sorting the distances in descending order and scanning to find the maximum E. Walk through a small example to validate the logic, and analyze time and space complexity.

Pro tip: Mention that the Eddington number can be computed in O(n log n) time by sorting, but if the maximum distance is small, a counting sort or bucket approach can achieve O(n) time. This shows awareness of trade-offs.

1. Clarify the problem

Restate the definition of the Eddington number and confirm assumptions, such as whether the list can be empty or contain zeros.

2. Discuss naive and optimized approaches

Explain a brute-force method (checking each possible E) and then propose a more efficient algorithm, such as sorting the distances in descending order.

3. Detail the algorithm

Describe the steps: sort the list descending, iterate through the sorted list, and find the largest index i (1-based) where the distance at that index is >= i. The Eddington number is the maximum such i.

4. Analyze complexity and edge cases

State the time complexity (O(n log n) due to sorting) and space complexity (O(1) extra if sorting in place). Discuss edge cases like empty list, all distances less than 1, or very large distances.

5. Test with examples

Walk through a small example, such as [5, 3, 2, 1], to demonstrate the algorithm and verify the result.

Key Points to Mention

  • Definition of Eddington number: largest E such that at least E days have distance >= E.
  • Sorting the distances in descending order simplifies the condition to finding the first index where distance < index+1.
  • Time complexity: O(n log n) for comparison-based sorting; can be O(n) with counting sort if max distance is bounded.
  • Space complexity: O(1) extra if sorting in place, otherwise O(n) for a new array.
  • Edge cases: empty list returns 0; if all distances are 0, Eddington number is 0.
  • Alternative approach: binary search on E, but sorting is more straightforward.

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