How Many Apples Can You Put into the Basket

How Many Apples Can You Put into the Basket

What is this problem about?

The How Many Apples Can You Put into the Basket coding problem is a simple resource management task. You have a basket that can carry a total weight of 5000 units. You are given an array representing the weights of several apples. Your goal is to maximize the number of apples you can put into the basket without exceeding the weight limit.

Why is this asked in interviews?

Virtu Financial and other firms use this "Easy" question to test basic algorithmic intuition, specifically the Greedy interview pattern. It checks if a candidate understands that to maximize the count of items, they should always prioritize the smallest items. It’s a test of foundational sorting and iteration logic.

Algorithmic pattern used

This problem follows the Greedy approach.

1. Sort the weights of the apples in ascending order.
2. Initialize a totalWeight to 0 and an appleCount to 0.
3. Iterate through the sorted weights.
4. For each apple, if adding its weight to totalWeight is $\le 5000$:
   • Add the weight.
   • Increment the count.
5. If adding the weight exceeds 5000, stop and return the count.

Example explanation

Apple weights: [900, 100, 500, 200, 1000]

1. Sort: [100, 200, 500, 900, 1000].
2. Take 100: Sum = 100, Count = 1.
3. Take 200: Sum = 300, Count = 2.
4. ... continue until the sum exceeds 5000. Result: The number of apples processed before the limit was hit.

Common mistakes candidates make

• Not Sorting: Attempting to pick apples in the original order or using a complex search algorithm.
• Off-by-one: Continuing to add apples even after the weight limit is reached.
• Inefficiency: Using a Max-Heap when a simple sort is more straightforward and has the same complexity for this task.

Interview preparation tip

Greedy algorithms are all about the "Local Optimum." In this case, picking the lightest apple available at each step is the local choice that leads to the global maximum count. Always mention why the greedy choice works—here, it's because any larger apple would "crowd out" potential smaller ones.