The original content didn't preserve enough detail to reconstruct what the actual problem was.
Clarify the problem by restating it and asking questions to confirm assumptions, then discuss multiple approaches from brute force to optimal, analyzing time and space complexity. Write clean, modular code with meaningful variable names, and test with edge cases while explaining your thought process throughout.
Pro tip: At Apple, emphasize practical trade-offs and real-world constraints—interviewers value engineers who consider performance, memory, and scalability beyond just passing test cases. Verbally walk through your code as you write it, as if pair programming, to demonstrate communication and collaboration skills.
Restate the problem in your own words, ask clarifying questions about input/output, constraints, and edge cases, and confirm your understanding with the interviewer.
Discuss brute force and optimized solutions, compare their time/space complexities, and choose the best approach based on constraints and trade-offs.
Outline your solution with pseudocode or comments, then write clean, modular code with meaningful names, explaining your logic as you go.
Walk through your code with a normal case, then test edge cases (empty input, single element, large input, duplicates) and fix any bugs.
State the final time and space complexity, and discuss potential optimizations or alternative approaches if time permits.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.