The greedy angle clicked pretty fast: always eat the apple that expires soonest.
Model the problem as scheduling unit-time jobs with deadlines, where each batch of apples is a job with a release day and an expiry day. Use a greedy strategy: process days in order and always eat the apple that expires soonest among available batches, which can be implemented efficiently with a min-heap keyed by expiry day.
Pro tip: Clarify the exact constraints first (e.g., whether batches arrive on specific days, whether you can eat an apple on its expiry day, and whether multiple batches can arrive on the same day). This shows attention to detail and avoids solving the wrong variant.
Ask about input format, constraints (n, number of batches), whether apples can be eaten on the expiry day, and if multiple batches can arrive on the same day. Confirm that you can eat at most one apple per day.
Recognize this as a scheduling problem: each batch is a job with a release time (arrival day) and a deadline (expiry day), and each day is a unit-time slot. The goal is to maximize the number of jobs scheduled.
Process days from 1 to n. On each day, add all batches that have arrived to a min-heap keyed by expiry day. If the heap is non-empty, eat the apple with the earliest expiry (pop from heap). This ensures you never miss an expiring apple if possible.
The algorithm runs in O((n + m) log m) time, where m is the number of batches, and O(m) space. Explain that each batch is inserted and removed at most once.
Walk through a small example, such as batches arriving on days 1, 2, 3 with different expiries, to verify the greedy choice works. Discuss edge cases like no apples, all apples expiring on the same day, or batches arriving after their expiry.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.