Minimum Cost to Split an Array
A hard-tier problem at 42% community acceptance, tagged with Array, Hash Table, Dynamic Programming. Reported in interviews at Indeed and 0 others.
Minimum Cost to Split an Array is a hard DP problem that shows up in Indeed's assessment rotations. It's the kind of problem where the brute-force approach feels logical at first, then times out, and you're stuck staring at a half-solution for the last five minutes of your OA. The twist is that you need to recognize how to track costs across splits efficiently without recomputing the same subproblems. Acceptance sits around 42%, which means most candidates either nail it or miss the DP structure entirely. If this problem hits your live assessment and you blank on the recurrence relation, StealthCoder solves it in seconds, invisible to the proctor.
Companies that ask "Minimum Cost to Split an Array"
Minimum Cost to Split an Array 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 an Amazon engineer who used it to pass JPMorgan's OA and system design loop.
Get StealthCoderThe core trick here is that a naive greedy or brute-force enumeration of all split points looks reasonable but explodes in complexity. You need dynamic programming where each state represents the minimum cost to split an array up to a given index. The real challenge is figuring out the transition: when you split at position i, you pay a cost based on the distinct elements in that range, then recurse on the remaining array. Hash tables shine here for counting distinct elements in subarrays without rebuilding from scratch. Many candidates get the DP skeleton right but fail to optimize the distinct-count lookup, turning an O(n^3) solution into a timeout. This is exactly where StealthCoder's real-time solution surfaces the efficient pattern you might otherwise miss under pressure.
Pattern tags
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Minimum Cost to Split an Array recycles across companies for a reason. It's hard-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 an Amazon engineer who used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Cost to Split an Array interview FAQ
Is Minimum Cost to Split an Array really as hard as the difficulty label says?+
Yes. The 42% acceptance rate confirms it's not a warm-up. Most people either see the DP structure immediately or they don't. The gap between a correct brute-force and an optimized solution is the difference between passing and timing out. It requires both DP reasoning and careful state management.
What's the main trap in this problem?+
Recomputing distinct element counts for overlapping subarrays. A naive approach recalculates for each (start, end) pair, tanking your runtime. You need to either precompute or use a smart incremental strategy with a hash table to count efficiently during the DP transition.
Do I need to know advanced techniques to solve this?+
Not advanced, but you need solid fundamentals: dynamic programming state definition, hash table usage for counting, and the ability to reason about cost accumulation across multiple transitions. If you're weak on any of those, this problem punishes you quickly.
Is this problem asked often at other tech companies?+
The data shows it primarily appears in Indeed's assessments. Structurally similar DP-plus-counting problems do show up elsewhere, but this exact formulation is less common across the broader FAANG interview circuit. It's more of a screening-round filter for Indeed.
How should I practice for this problem type?+
Work through DP problems that combine state transitions with hash table lookups. Focus on understanding how to avoid redundant calculations when counting or aggregating properties of subarrays. Then practice writing clean code for the transition logic under time pressure.
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