How Many Apples Can You Put into the Basket
A easy-tier problem at 67% community acceptance, tagged with Array, Greedy, Sorting. Reported in interviews at Virtu Financial and 0 others.
You've got an easy problem that looks like a fruit-packing problem but is really testing whether you can spot a greedy pattern. Virtu Financial has asked this one. The trick isn't in the data structures, it's in understanding that you don't need to overthink the selection process. If the problem statement gives you weights, costs, or capacities, the optimal answer often just means picking the items that fit best according to a simple rule. This is the kind of problem where candidates either solve it in 90 seconds or spin in circles trying to model it as a harder problem than it is. If you blank on the greedy insight during your live assessment, StealthCoder runs invisibly and surfaces the working approach.
Companies that ask "How Many Apples Can You Put into the Basket"
How Many Apples Can You Put into the Basket is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Built by a senior engineer who knows the OA is theater. This is the script.
Get StealthCoderThe core pattern here is recognizing that greedy works. Sort by whatever dimension limits your choice (usually by size or weight ascending), then greedily pack items until you hit the constraint. The trap is overthinking it: candidates often assume this needs dynamic programming or complex state tracking when a single pass through sorted items is enough. Array operations and sorting are mechanical. The real skill test is pattern recognition: knowing when greedy is valid. Common misfire is trying to optimize locally without seeing that the global optimal just follows from a sorted order. During the live OA, if you can't immediately articulate the greedy rule, StealthCoder solves it while you stay undetected, keeping your score clean.
Pattern tags
You know the problem.
Make sure you actually pass it.
How Many Apples Can You Put into the Basket recycles across companies for a reason. It's easy-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Built by a senior engineer who knows the OA is theater. This is the script. Works on HackerRank, CodeSignal, CoderPad, and Karat.
How Many Apples Can You Put into the Basket interview FAQ
Is this really an easy problem or does the difficulty rating lie?+
The 67% acceptance rate confirms it's genuinely easy. The shape of the problem is straightforward once you spot the greedy pattern. Most candidates who fail miss the insight entirely rather than hitting a tough implementation. If you drill sorting and basic array iteration, you can solve this cold.
How does greedy apply to apple/basket problems?+
Greedy works when you can sort by a clear metric (size, weight, or value) and picking the best available item at each step guarantees the global optimum. For baskets, this usually means sorting by size and packing smallest items first or vice versa, depending on the constraint. The problem statement will hint at which direction.
What's the most common mistake candidates make?+
Treating it as an optimization problem that needs backtracking or DP when a single sorted pass solves it. Candidates also sometimes misread the constraint itself, packing wrong items because they didn't nail down whether you're maximizing count or total weight. Read the constraint twice.
Does Virtu Financial ask harder variants of this problem in later rounds?+
That data isn't available, but greedy problems at one company often appear as warm-ups in earlier loops. Mastering the pattern here matters because it trains your instinct for when greedy works, a skill tested across many companies and difficulty levels.
Should I use extra space for sorting or sort in place?+
The problem likely doesn't specify, so sorting in place with a built-in sort is standard and safe. If the input array can't be modified, create a copy first. This is implementation detail that doesn't change the algorithm, so don't get stuck on it during the live OA.
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