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LeetCode Card 275 — Heaps and Priority Queues / Check

Heaps And Priority Queues — BASIC step map

Pattern signal

This pattern usually appears when the prompt involves repeated access to current min/max or top-k items under ongoing updates. Kth Largest Element, Top K Frequent, Merge K Sorted Lists, and scheduling problems frequently use heaps.

Worth pausing here during practice.

What Check means here

In BASIC, the Check step is where you dry-run the result on edge cases, confirm complexity, and inspect whether the invariant actually held. For Heaps and Priority Queues, that matters because the pattern only becomes useful once the candidate is explicit about what is being tracked, reduced, or preserved.

Interview move

A strong move is to review and stress-test before you hand the answer over. In this pattern family, say out loud what representation makes the problem easier: the map entry, the pointer invariant, the recursion contract, the queue contents, or the DP state. That keeps the implementation attached to a reason.

Common miss

Candidates pick a heap without first defining what priority each entry should encode. BASIC reduces that risk because the stage sequence forces you to earn the implementation instead of jumping straight into it.

BASIC prompt

“Given that this looks like Heaps and Priority Queues, what is the simplest way to dry-run the result on edge cases, confirm complexity, and inspect whether the invariant actually held?”

The verification mindset
Check isn't debugging — it's verification. You're not looking for bugs you expect. You're systematically confirming that what you built matches what you planned. Walk through a small example. Check boundary conditions. State the time and space complexity. Each one is a trust signal.

References

S10 S12 S13

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