Coursera·Backend Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Coursera backend engineer interview with a coding question around election ballot processing. Pretty clean problem on the surface but the tie-breaking condition is the kind of thing you can easily forget to handle under pressure.

Questions Asked (1)

You're given a map where each key is a tuple representing a voter's full candidate ranking (most preferred first) and each value is how many voters submitted that exact ranking. Find the candidate with the most first-choice votes. If there's a tie, return the lexicographically smallest name among the tied candidates.

Algorithms & Data Structures

Author's notes

The core aggregation part is straightforward, just pull index 0 from each tuple and sum up the counts.

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AI HintsAI Generated

Suggested Approach

Iterate through the map entries, extract the first element of each ranking tuple, and accumulate the vote counts per candidate in a dictionary. Then, find the maximum count and among candidates with that count, return the lexicographically smallest name. This is a straightforward O(N) time and O(C) space solution, where N is the number of distinct rankings and C is the number of candidates.

Pro tip: Clarify edge cases upfront: what if the map is empty? What if a ranking tuple is empty? Also, mention that Python's tuple comparison is lexicographic, so you can use min() directly on the tied candidates. This shows attention to detail and robustness.

1. Understand the input and output

Confirm that the map keys are tuples of candidate names in preference order, and values are vote counts. The output is a single candidate name (string).

2. Aggregate first-choice votes

Initialize a dictionary to count votes per candidate. For each ranking tuple, take the first element and add the corresponding vote count to that candidate's total.

3. Find the maximum vote count

Determine the highest vote total among all candidates. This can be done by scanning the aggregated dictionary or using max() on the values.

4. Resolve ties lexicographically

Collect all candidates with the maximum vote count. If there's more than one, return the lexicographically smallest name (e.g., using min() on the list).

5. Handle edge cases

Consider empty input, empty ranking tuples, or candidates with zero votes. Discuss how to handle these gracefully, such as returning None or raising an exception.

Key Points to Mention

Time and space complexity: O(N) time to iterate through the map, O(C) space for the vote count dictionary, where N is number of distinct rankings and C is number of candidates.
Using a dictionary (hash map) to accumulate votes is efficient and straightforward.
Lexicographic comparison: Python's string comparison is lexicographic, so min() works directly.
Edge cases: empty map, empty ranking tuples, or ties involving multiple candidates.
Alternative approaches: sorting candidates by vote count and name, but that would be O(C log C) which is less efficient than a single pass.
Clarify assumptions: e.g., all rankings are non-empty, candidate names are strings, vote counts are positive integers.

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