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Heap
A tree on the inside; revisits earlier problems with the new tool.
0/5 lessons · exam: 0/30%
Lessons
- ✓01
Recognizing heap problems
What a heap is, the heap property, push/pop in O(log n), and when it is the tool.
- ✓02
Pattern 1: Top-K with a heap of size K
Keeping only the K best in a fixed-size heap — the k-th largest in O(n log k).
- ✓03
Pattern 2: Merging K sources (k-way merge)
The heap always picks the next smallest among K lists — merge k revisited.
- ✓04
Pattern 3: Two heaps (median of a stream)
Splitting the data into two balanced halves to find the median in O(log n).
- ✓05
Synthesis: which pattern to use?
The Heap section's decision tree and the general quiz before the final exam.
1 easy + 1 medium + 1 hard — unseen problems
With hidden test cases, just like the real LeetCode. This is where you confirm you can leave the section solving any problem of the topic.