Start by clarifying the problem requirements and constraints, then identify the core entities and their relationships to define classes and interfaces. Choose appropriate data structures and algorithms, implement the key methods, and discuss trade-offs in terms of time/space complexity and extensibility.
Pro tip: Demonstrate maturity by explicitly discussing trade-offs and considering edge cases, scalability, and maintainability from the start. Also, relate your design to real-world systems or patterns you've encountered.
Ask questions to understand the problem scope, expected operations, performance requirements, and any constraints. This ensures you design the right system.
Determine the main classes/objects, their attributes, and how they interact. Define interfaces and responsibilities clearly.
Choose the most efficient data structures and algorithms for the required operations, justifying your choices based on complexity and use cases.
Write the key methods, ensuring they handle edge cases and are optimized. Explain the algorithmic logic step by step.
Analyze the pros and cons of your design, including time/space complexity, scalability, and how it can be extended or modified.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.