⛰️ Heap
Heaps (priority queues) excel at "what is the smallest / largest right now?" questions. Top-K, scheduling, merging sorted streams, and running medians all reduce to one or two heaps.
This category contains 2 problems. Use the patterns below to recognize what's being asked, then jump to the problem list at the bottom.
🧠 Key Patterns
- Top-K Elements — Min-heap of size K for largest-K, max-heap for smallest-K.
- Merge K Sorted Lists/Streams — Min-heap keyed on current head value.
- Running Median (two heaps) — Max-heap for lower half, min-heap for upper half.
- Task Scheduling — Max-heap on remaining frequency.
- Dijkstra — Min-heap on tentative distance.
⚠️ Common Pitfalls
- C#
PriorityQueue<TElement, TPriority>is a min-heap by default — invert priority for max-heap. - Heapify-up vs heapify-down: standard library handles this, but write it once by hand.
📚 Study Resources
📺 Videos
📖 Books
- Introduction to Algorithms (CLRS) — Ch. 6 (Heapsort), Ch. 19 (Fibonacci heap)
🌐 Articles & References
💻 All Heap Problems
K Closest Points to Origin
LeetCode 1014 | Difficulty: Medium
Sort Characters By Frequency
LeetCode 451 | Difficulty: Medium