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Coursera·Backend Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Coursera backend engineer interview with a voting algorithm problem. Two parts to the same question, one straightforward and one that actually requires thinking through the elimination logic carefully.

Questions Asked (2)

Q1

Given ballots represented as a dictionary mapping ranked candidate tuples to voter counts, implement a popular vote function that returns the candidate with the most first-place votes.

Algorithms & Data Structures
Author's notes

Pretty mechanical once you see it.

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AI HintsAI Generated

Suggested Approach

Clarify the input structure and edge cases, then iterate through the dictionary to tally first-place votes for each candidate. Return the candidate with the highest count, handling ties or empty input as specified.

Pro tip: Mention that you would confirm tie-breaking rules and whether the function should return all tied candidates or a single winner, showing attention to real-world ambiguity.

1. Clarify requirements

Ask about tie-breaking, empty ballots, and whether the input dictionary is guaranteed to be non-empty. Confirm the expected return type (e.g., string, list).

2. Design the algorithm

Explain that you will iterate over each key (ranked candidate tuple) and extract the first element. Use a hash map to accumulate counts for each candidate.

3. Implement and handle edge cases

Write code that handles empty input, ties, and candidates with zero first-place votes. Consider using a defaultdict or Counter for efficiency.

4. Analyze complexity

State that time complexity is O(n) where n is the number of ballot entries, and space complexity is O(k) where k is the number of unique candidates.

5. Test with examples

Walk through a sample input to verify correctness, including a tie scenario if applicable.

Key Points to Mention

  • Input is a dictionary mapping ranked candidate tuples to voter counts.
  • First-place vote is the first element of each tuple.
  • Use a hash map (e.g., Python dict or Counter) to tally votes.
  • Handle ties by either returning all tied candidates or following a specified rule.
  • Consider edge cases: empty dictionary, single candidate, multiple candidates with zero votes.
  • Time complexity O(n) and space complexity O(k) where n is number of entries and k is number of candidates.

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

Q2

Using the same ballot structure, implement a ranked-choice voting algorithm that eliminates the last-place candidate each round and redistributes their votes until someone clears 50%.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This is where I fumbled a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the ballot structure and assumptions (e.g., number of candidates, handling of ties, exhausted ballots). Then outline the algorithm: count first-choice votes, check for majority, eliminate the lowest candidate, redistribute their votes to the next non-eliminated choice, and repeat. Finally, discuss trade-offs and edge cases.

Pro tip: Mention that you would use a priority queue or efficient data structures to track vote counts and candidate elimination, and that you would handle exhausted ballots by either reducing the total or treating them as abstentions. This shows awareness of real-world implementation concerns.

1. Clarify requirements and assumptions

Ask about the ballot structure (e.g., list of candidate rankings per voter), number of candidates, and how to handle ties and exhausted ballots. Confirm the majority threshold (50% of active votes or total votes).

2. Design the algorithm

Describe the round-based process: tally first-choice votes, check if any candidate exceeds 50%, if not, identify the candidate with the fewest votes, eliminate them, and redistribute their votes to the next preferred non-eliminated candidate.

3. Implement efficiently

Choose data structures: a list of ballots, a map of candidate to vote count, and a set of eliminated candidates. For each ballot, maintain an index of the current top choice. Use a priority queue or sorted list to quickly find the lowest candidate.

4. Handle edge cases and termination

Address ties for elimination (e.g., break by random or predefined order), exhausted ballots (no remaining candidates), and termination conditions (majority reached or only two candidates left).

5. Analyze complexity and trade-offs

Discuss time complexity (e.g., O(R * V * C) where R is rounds, V voters, C candidates) and space complexity. Mention potential optimizations like precomputing rankings or using a heap.

Key Points to Mention

  • Ballot structure: each voter provides an ordered list of candidates.
  • Majority threshold: >50% of active (non-exhausted) votes.
  • Elimination and redistribution: transfer votes to next non-eliminated choice.
  • Handling exhausted ballots: either reduce total active votes or treat as abstentions.
  • Tie-breaking for elimination: random, alphabetical, or based on previous round.
  • Complexity: O(R * V * C) time, O(V * C) space; optimizations with heaps.

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