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mediumAdvancedLeetCode#filter safe items

Merge triplets to form target triplet

Decide whether element-wise maximums of some triplets can equal a target, by merging only the triplets that never exceed it.

The Runtime Theory Team1 min read
Taught inExchange argumentsPro — members onlyTo prove a greedy order is optimal, take any solution that differs from it, swap two elements to make it more like the greedy one, and show the swap never makes it worse. Repeat until the two agree.
Solve it

Solving happens on the judge — come back and mark it done

Sample cases

intriplets = [[2, 5, 3], [1, 8, 4], [1, 7, 5]], target = [2, 7, 5]

outtrue

intriplets = [[3, 4, 5], [4, 5, 6]], target = [3, 2, 5]

outfalse

intriplets = [[2, 5, 3], [2, 3, 4], [1, 2, 5], [5, 2, 3]], target = [5, 5, 5]

outtrue

Merging two triplets takes the maximum in each position. Return whether some sequence of merges can produce the target.

Before you code

Maximums only grow. A triplet with any value above the target's in that position can never be used. Every other triplet can be merged without harm.

Hints

  1. Skip triplets that exceed the target anywhere.
  2. Merge all the rest, or just record which target positions some safe triplet matches exactly.
  3. The answer is whether all three positions are matched.

Production & complexity notes

When solving Merge triplets to form target triplet on LeetCode (medium), always state your loop or recursion invariant before writing code. Verify how your chosen data structure behaves on degenerate inputs (single-element inputs, all-duplicate keys, strictly monotonic sequences, or maximum constraint sizes up to $10^5$ elements). In production interviews, pair your implementation with an explicit time and auxiliary space complexity proof, explain why alternative brute-force approaches violate the latency budget, and trace how cache locality and memory allocation overhead affect wall-clock throughput on real hardware. Review the step-by-step memory trace in Exchange arguments to reinforce the underlying pattern.

What it practices

Arguing that a greedy choice never hurts, from Exchange arguments.

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