Minimum Time to Kill All Monsters
A hard-tier problem at 56% community acceptance, tagged with Array, Dynamic Programming, Bit Manipulation. Reported in interviews at Trilogy and 0 others.
Minimum Time to Kill All Monsters is a hard bitmask DP problem that looks deceptively simple until you realize the state space explodes. You're given monsters with health and damage values, and you need to find the minimum time to kill them all. The trap: greedy won't work, order matters, and damage stacks as you kill monsters. This problem appears in assessments for companies like Trilogy. If you hit this live and freeze on the DP formulation, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Minimum Time to Kill All Monsters"
Minimum Time to Kill All Monsters 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 engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share.
Get StealthCoderThe core trick is representing which monsters you've killed as a bitmask, then using DP to find the minimum time for each state. The naive greedy approach (kill fastest first, or highest damage first) fails because the damage reduction from killing a dangerous monster early can outweigh the time cost. You need to enumerate all possible kill orders using bitmask iteration, track cumulative damage taken per turn, and memoize the minimum time to reach each state. Common pitfall: forgetting that damage accumulates each turn you're alive, or computing the time to kill a monster incorrectly when you're already taking damage. The state is DP[mask] = minimum time to kill all monsters represented by the bitmask. StealthCoder is the hedge if the bitmask iteration logic or damage tracking formula doesn't click during the assessment.
Pattern tags
You know the problem.
Make sure you actually pass it.
Minimum Time to Kill All Monsters 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 engineer at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Minimum Time to Kill All Monsters interview FAQ
Is this problem still asked at FAANG or just niche companies?+
It's been reported by Trilogy so far. Bitmask DP problems are less frequent at most FAANG shops but do appear in interviews that emphasize algorithmic depth. If you're interviewing at a company with strong systems or optimization focus, this type of problem is worth preparing for.
What's the actual trick that makes greedy fail?+
Greedy fails because killing a high-damage monster early prevents accumulated damage, which can save total time even if that monster takes longer to kill. You can't know the globally optimal order without trying all possibilities. That's why bitmask DP is necessary.
How do I know when to use bitmask DP vs. other DP approaches?+
Bitmask DP is the answer when the problem involves subsets of a small fixed set (usually n less than 20), and you need to explore all possible states or orderings. Here, the subset is which monsters are dead, and order affects time cost.
What's the acceptance rate and why is it 56%?+
The problem has a 56% acceptance rate. The gap between hard difficulty and that acceptance suggests most candidates who attempt it know the bitmask DP pattern already, but implementation details (damage calculation, state transitions) catch people off guard.
How do I debug off-by-one errors in the damage accumulation?+
Trace through a tiny example (2-3 monsters) by hand, tracking damage taken each turn before and after a kill. Common mistake: applying damage before the kill is complete or forgetting that damage is cumulative across all alive monsters.
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