Pretty straightforward once you realize you only look at the first element of each ballot.
Start by clarifying the input format and edge cases, then outline a hash map approach to tally first-choice votes. After tallying, find the maximum count and collect all candidates with that count, returning the lexicographically smallest among them.
Pro tip: Mention that you'd handle empty ballots or no candidates gracefully, and discuss how the solution scales if the number of candidates or ballots grows large.
Ask about input format (e.g., list of lists of strings), tie-breaking rules, and what to return if there are no ballots. Confirm that lexicographic order is based on candidate names.
Use a hash map (dictionary) to count first-choice votes for each candidate. Iterate through each ballot and increment the count for the first candidate.
Find the maximum vote count. Collect all candidates with that count, then return the lexicographically smallest candidate name.
State time complexity O(N) where N is number of ballots, and space O(C) for C candidates. Walk through a small example and edge cases like ties and empty input.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
First, clarify the input format and tie-breaking rules, then outline a round-by-round simulation where you tally first-choice votes, check for a majority, and eliminate the candidate with the fewest votes (breaking ties by removing the lexicographically largest). Emphasize efficiency by using a data structure that supports fast vote redistribution, and discuss time/space complexity.
Pro tip: Mention that you would validate the input and handle edge cases like all candidates tied or a single candidate, and that you can optimize by precomputing ballot rankings to avoid re-scanning all ballots each round.
Confirm the ballot input format (e.g., list of ranked candidate lists), the majority threshold (strictly >50% of active votes), and tie-breaking rule (eliminate lexicographically largest among those with fewest votes). Ask about empty ballots, exhausted votes, and whether all candidates must be ranked.
Outline a loop that runs until a candidate exceeds 50% or only one remains. In each round, tally first-choice votes from active ballots, check for a winner, and if not, identify the candidate(s) with the fewest votes and eliminate the lexicographically largest among them.
Use a hash map to count votes per candidate and a list of active candidates. For each ballot, maintain a pointer to the current top choice; when a candidate is eliminated, advance the pointer to the next non-eliminated candidate. This avoids re-scanning entire ballots each round.
Write pseudocode or code for the simulation, ensuring tie-breaking is correctly applied. Test with simple cases (single candidate, majority in first round) and complex cases (multiple rounds, ties, exhausted ballots).
Discuss time complexity: O(R * B) naive vs. O(B + R * C) with pointers, where R is rounds, B ballots, C candidates. Mention space complexity O(B + C). Trade-offs: simplicity vs. performance, and how to handle large inputs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.