Start by clarifying the 5 sub-questions and their dependencies, then design a modular simulation with clear interfaces. Implement incrementally, validating each part before moving on, and discuss trade-offs (e.g., performance vs. accuracy) at each step.
Pro tip: Proactively discuss how you would test and validate each sub-question, including edge cases and scalability, to demonstrate engineering maturity.
Ask questions to understand the expected inputs, outputs, and constraints for each sub-question. Confirm the disease model (e.g., SIR), population structure, and time steps.
Outline a modular design with separate components for population, disease states, and simulation loop. Define interfaces to allow incremental extension.
Code each sub-question one by one, starting with the simplest. Test each part thoroughly before integrating with the next.
For each sub-question, discuss time/space complexity, accuracy vs. performance, and potential optimizations (e.g., spatial partitioning, parallelization).
Run simulations with known scenarios to validate results. Discuss how to handle edge cases and scale to larger populations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.