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Coursera·Backend Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Coursera backend interview with a pretty involved algorithmic problem around Instant-Runoff Voting. The question had enough edge cases that you really had to think through the procedure carefully, and clarifying tie-break behavior with the interviewer was part of the exercise.

Questions Asked (1)

Q1

You're given a map of election ballots where each key is a tuple representing a voter's full candidate ranking (most preferred first) and each value is the count of voters with that exact ranking. Implement the Instant-Runoff Voting algorithm: repeatedly tally first-choice votes, declare a winner if someone exceeds 50% of remaining votes, otherwise eliminate the last-place candidate and redistribute their ballots to the next ranked choice. What are the tie-break rules for elimination and for the majority check?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The redistribution logic is where I got a bit tangled.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the tie-break rules for both elimination and majority check, as they are critical to a deterministic implementation. Then outline the IRV algorithm step-by-step, emphasizing how to handle ties and edge cases. Finally, discuss the time complexity and potential optimizations for large datasets.

Pro tip: Mention that tie-break rules should be explicitly defined and documented, as different implementations (e.g., random, alphabetical, or based on previous rounds) can lead to different outcomes, which is crucial for reproducibility and fairness.

1. Clarify Tie-Break Rules

Explicitly state the tie-break rules for elimination and majority check. For elimination, common rules include eliminating the candidate with the fewest first-choice votes; if tied, use a secondary criterion like lowest candidate ID or random selection. For majority check, if no candidate exceeds 50%, proceed to elimination; if exactly 50%, typically no winner yet.

2. Outline IRV Algorithm

Describe the iterative process: tally first-choice votes from remaining ballots, check for majority, eliminate last-place candidate, redistribute ballots to next ranked choice, and repeat until a winner emerges.

3. Handle Edge Cases

Discuss scenarios like all candidates tied, ballots with no remaining preferences, and the possibility of a tie in the final round. Explain how your tie-break rules resolve these.

4. Analyze Complexity and Optimizations

Mention the time complexity (e.g., O(n*m) where n is number of ballots and m is number of candidates) and suggest optimizations like using a priority queue or precomputing rankings.

5. Summarize and Conclude

Recap the key points, emphasizing the importance of deterministic tie-break rules for correctness and fairness.

Key Points to Mention

  • Definition of majority: more than 50% of remaining votes (excluding exhausted ballots).
  • Elimination tie-break: typically eliminate the candidate with the fewest votes; if tied, use a deterministic rule like lowest candidate ID or random with seed.
  • Majority tie-break: if no candidate exceeds 50%, eliminate; if exactly 50%, no winner yet.
  • Handling exhausted ballots: ballots with no remaining preferences are removed from further counts.
  • Time complexity: O(n*m) where n is number of ballots and m is number of candidates, with potential optimizations.
  • Importance of documenting tie-break rules for reproducibility and fairness.

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