← Microsoft Interview Insights
First, clarify the exact rules for calculating final scores, including any edge cases like missing assignments or extra credit. Then, outline an algorithm that processes the dataset efficiently, and discuss potential optimizations and test cases.
Pro tip: Demonstrate a test-driven mindset by walking through concrete examples and edge cases before coding, and mention how you would validate the solution with unit tests.
Ask questions to fully understand the scoring rules, data format, and expected output. Confirm edge cases such as missing scores, weighting, and rounding.
Choose an appropriate data structure (e.g., hash map for student records) and outline steps to compute scores. Consider time and space complexity.
Identify and plan for scenarios like empty datasets, invalid inputs, or ties. Ensure the solution is robust.
Write clean, modular code and test with sample inputs, including edge cases. Discuss how you would verify correctness.
If needed, suggest optimizations (e.g., sorting, caching) and explain trade-offs between simplicity and performance.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.