6 articles
Master LeetCode 315 — one of the most common FAANG hard problems. Learn why a naive O(n²) scan fails at scale, how merge sort secretly counts inversions as a side effect, and how to trace through every swap on paper. Includes both brute-force and optimal solutions in Python and JavaScript, a full complexity table, and the three follow-up problems that frequently appear in the next interview round.
LeetCode 4 is one of the most feared Hard problems in FAANG interviews. Learn exactly why the partition insight works, trace through a full binary search dry run, understand the five common bugs that cause silent wrong answers, and walk away with production-quality Python and JavaScript solutions.
LeetCode 493 trips up even strong candidates because the count step must happen before the merge step — not during it. Learn exactly why that ordering matters, trace through a full dry run on [1,3,2,3,1], understand the five most common bugs, and walk away with clean Python and JavaScript solutions you can reproduce under pressure.
Master LeetCode 327 — Count of Range Sum — with deep intuition, a visual dry run, brute-force to O(n log n) merge sort progression, and real interview follow-ups covering BIT, LC 315, and LC 493.
Count subarrays whose sum lies in [lower, upper] using merge sort on prefix sums in O(n log n). Understand the divide-and-conquer counting trick that makes an O(n^2) brute-force drop to linearithmic time.
LC 427 Construct Quad Tree builds a spatial partitioning tree from a 2D binary grid by recursively splitting non-uniform regions into four quadrants. This divide-and-conquer problem is tested at Amazon and Google and models real-world image compression and spatial indexing.