7 articles
Master two optimal approaches to merge k sorted linked lists: min-heap for O(n log k) time and divide-and-conquer for O(n log k) with lower constant factors. A top-tier interview problem at Amazon, Google, Facebook, Microsoft, and Uber that tests your mastery of heaps and recursive merging.
Master Prim's algorithm for Minimum Spanning Tree: grow a single tree from any starting vertex by repeatedly attaching the cheapest crossing edge using a min-heap. The dense-graph counterpart to Kruskal, asked at Google, Amazon, and Microsoft.
LeetCode 347 asks for k most frequent elements with a constraint: beat O(n log n). Learn why naive sort fails, how a min-heap of size k achieves O(n log k), and the elegant bucket sort insight that delivers true O(n) — with full visual dry run, common mistakes, and Python/JavaScript solutions for all three approaches.
Master LC 871 with two complementary strategies: a greedy max-heap that asks "which station gives me the most fuel when I am stuck?" in O(n log n), and a DP table that asks "what is the farthest I can reach with exactly k stops?" in O(n²). Both are asked at Amazon and Google. Learn the intuition, see a full dry run, and understand when each approach fits.
LC 1167 Minimum Cost to Connect Sticks applies Huffman coding greedy with a min-heap. Always merge the two cheapest sticks first — a classic greedy pattern with a provable exchange argument that Amazon uses to test priority queue fluency.
Design a simplified Twitter with follow/unfollow and a news feed that returns the 10 most recent tweets across followed users — combining hash maps, social graph storage, and k-way heap merging.
Solve LeetCode 295 Find Median from Data Stream with two heaps (max-heap for low half, min-heap for high half) giving O(log n) addNum and O(1) findMedian. A FAANG streaming classic.