Find Minimum Cost to Remove Array Elements
A medium-tier problem at 19% community acceptance, tagged with Array, Dynamic Programming. Reported in interviews at DE Shaw and 0 others.
Find Minimum Cost to Remove Array Elements shows up in DE Shaw's interviews and it hits different from typical array problems. With an 18.5% acceptance rate, this is a real sieve. You're not doing a simple loop here. The problem forces you to think backwards or spot a hidden dependency between removals. Most candidates see the word "cost" and jump to greedy. That fails. The trick is realizing that removal order matters because each removal changes what's available next. If you blank on the pattern during the live assessment, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Find Minimum Cost to Remove Array Elements"
Find Minimum Cost to Remove Array Elements 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 trap is treating each removal independently. The actual insight is that cost compounds based on which elements are still present. This is a Dynamic Programming problem disguised as an array question. You'll need to either recurse with memoization or build a DP table that tracks the state of remaining elements and cumulative cost. The state space can be large, so optimization matters. Some candidates try bitmask DP if the array is small, others use interval DP depending on the cost function. The acceptance rate reflects that the pattern isn't obvious from the problem statement alone. You have to see that removal order creates dependencies. If you haven't drilled this exact pattern before and you hit it live, StealthCoder is your hedge. It reads the problem, recognizes the DP structure, and gives you working code while you stay invisible.
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Find Minimum Cost to Remove Array Elements recycles across companies for a reason. It's medium-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.
Find Minimum Cost to Remove Array Elements interview FAQ
Why is the acceptance rate so low for a Medium problem?+
The problem disguises itself as a simple array task but requires recognizing a hidden DP structure. Most candidates default to greedy or simulation, which fails. The trick isn't spelled out, so you either see the pattern or you don't. That gap explains the 18.5% rate.
Is this still asked at DE Shaw or just a legacy question?+
De Shaw has reported this problem in recent hiring cycles. If you're interviewing there, assume it's still in rotation. Even if it doesn't appear in your loop, the DP pattern it teaches transfers directly to other cost-optimization problems they ask.
What's the difference between this and a standard DP array problem?+
Standard array DP usually optimizes a single metric like max sum or min steps. This one has a removal mechanism that changes what's available for future removals. That dependency chain is what makes it harder. You're not just optimizing output; you're optimizing process.
Should I use memoization or tabulation for this one?+
That depends on the state representation. If the problem allows bitmask representation and the array is small (under 20 elements), bitmask DP with memoization is clean. For larger inputs, you might need interval DP or a bottom-up table. The input spec matters here.
How do I know if I'm on the right approach during the interview?+
If you're simulating removals step-by-step without memoization, you're probably wrong. A correct DP solution should avoid recomputing the same state twice. If you can't explain why removal order changes the answer, rethink the approach.
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