HeapEvidence Contributing
Heap for Top-K / Kth Element
Maintain a fixed-size heap to track the k largest/smallest/most-frequent elements seen so far.
Practice Problems: 12
Difficulty: 2 Easy·7 Medium·3 Hard
Algorithmic Intuition & Recognition
The Heap for Top-K / Kth Element technique is applied when tackling problems characterized by specific invariants in the problem state or constraints:
- Core Strategy: Maintain a fixed-size heap to track the k largest/smallest/most-frequent elements seen so far.
- When to use: Look for opportunities where repeated re-computation can be replaced by maintaining monotonic properties, state windows, or relational pointers.
- Interview Signal: Demonstrating this pattern shows mastery of Heap foundations, reducing worst-case algorithmic complexity.