Spent 40 minutes on this and barely scraped through with 10 minutes left.
Clarify the definition of a valid string (e.g., every 'a' must have a later 'b' or 'c', and every 'b' must have a later 'c'), then use a greedy two-pass approach to count unmatched characters. The minimum additions equal the number of unmatched 'a's and 'b's that cannot be paired with later characters.
Pro tip: Emphasize that the greedy solution is optimal because each unmatched character must be fixed by adding a character after it, and adding one character can resolve at most one unmatched character. This shows you understand the proof of optimality, not just the algorithm.
Ask the interviewer to confirm the definition of a valid string: typically, every 'a' must have a 'b' or 'c' after it, and every 'b' must have a 'c' after it. Also confirm that we can only add characters, not remove or replace.
Scan the string from right to left, keeping counters for unmatched 'b's and 'a's. When you see a 'b', increment the 'b' counter; when you see an 'a', if there is an unmatched 'b', pair them (decrement 'b'), otherwise increment the 'a' counter. The answer is the sum of unmatched 'a's and 'b's.
Walk through the two-pass or single-pass right-to-left approach, showing how each character is processed and how the counters change. Use a small example to illustrate.
State that the solution runs in O(n) time and O(1) space, which is optimal. Mention that a brute-force approach would be exponential, so this is a significant improvement.
Cover edge cases like empty string, all 'a's, all 'c's, and strings already valid. Discuss why the greedy approach works and whether there are alternative interpretations of 'valid' that would change the solution.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Knocked this one out in about 10 minutes, no drama.
Since the details of the second coding problem are not specified, focus on demonstrating a structured problem-solving process. Start by clarifying the problem statement and constraints, then discuss your approach, trade-offs, and complexity before coding. Emphasize testing and edge cases to show thoroughness.
Pro tip: Even if you solved it quickly, take time to explain your reasoning and consider alternative approaches. Interviewers value clear communication and the ability to optimize, not just speed.
Ask questions to understand inputs, outputs, constraints, and edge cases. Confirm assumptions with the interviewer.
Outline your planned algorithm, including data structures and why they are suitable. Mention time and space complexity.
Briefly discuss other possible approaches and trade-offs, showing you can evaluate multiple solutions.
Write clean code, then walk through test cases including edge cases to verify correctness.
If time permits, discuss potential optimizations or improvements, and summarize key takeaways.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.