66 articles
Master the write pointer pattern — the canonical technique for in-place array modification. Full walkthrough of LeetCode 26 with visual dry run, common mistakes, and the LC 80 generalization. Python and JavaScript solutions included.
Find the one element that appears once while every other appears twice. The XOR bit trick delivers O(n) time and O(1) space — no extra memory, no sorting. Master the three XOR properties that make it work, then see how interviewers escalate to Single Number II and III.
Two problems, one pair of concepts: LC 349 asks for the unique intersection (HashSet), LC 350 asks for the frequency-aware intersection (HashMap). Master all three approaches for LC 349 — HashSet, sort+two pointers, binary search — then learn why the follow-up questions on LC 350 are what Google and Amazon actually care about: sorted input, skewed sizes, and data that does not fit in memory.
Master cheatsheet of all 100 Arrays & Strings problems: patterns, time/space complexity, and MAANG company tags in one place.
Master Pascal's Triangle (LeetCode 118 & 119) by understanding the binomial coefficient connection, the row-by-row DP pattern, space-optimized O(k) single-row generation, and five hidden mathematical properties that show up in Unique Paths, Coin Change, and beyond.
Master LeetCode 242 Valid Anagram with three approaches — sort O(n log n), 26-element frequency array O(n)/O(1), and HashMap O(n)/O(k). Includes a visual dry run, the critical Unicode follow-up, and the direct connection to Group Anagrams (LC 49).
LeetCode 344 is the canonical two-pointer problem — and it shows up at Meta, Microsoft, and Amazon as both a standalone question and as the foundation for palindrome checks, anagram detection, and rotate-array problems. Learn the in-place swap pattern deeply, trace through every edge case, and master the follow-ups that separate passing candidates from standout ones.
LeetCode 387 is deceptively simple — but the way you solve it, explain it, and handle its follow-ups separates candidates who get the offer from those who do not. Master the two-pass frequency map, understand why O(1) space is possible, and be ready for every streaming and ordering twist Amazon throws at you.
Master LeetCode 125 — Valid Palindrome with the O(1)-space two-pointer technique. Learn why every FAANG loop starts here, visualize the pointer walk on a classic example, avoid the four most common pitfalls, and unlock the palindrome follow-up chain: LC 680, LC 5, and LC 647.
LeetCode 14 appears deceptively simple — until the interviewer asks you to do it without sorting, then with binary search, then on a stream of words. Master all three approaches (vertical scan, horizontal fold, binary search on length), understand exactly why each one works, and walk into your Google screen ready for every escalation.
Count primes below n sounds trivial — until your naive solution times out on n=5,000,000. Master the Sieve of Eratosthenes, one of the most elegant algorithms in all of computer science, and learn the exact intuition that separates candidates who pass Amazon and Google screens from those who do not.
LeetCode 268 hides four distinct valid solutions behind a deceptively simple problem. Learn Sort, HashSet, Gauss Formula, and XOR — understand exactly why each exists, when interviewers ask for each one, and why XOR is the most elegant answer in the room.
The Boyer-Moore Voting Algorithm solves LeetCode 169 in O(n) time and O(1) space using a brilliantly counterintuitive cancellation trick. Learn the proof, the dry run, all four approaches, and why interviewers love this problem — plus the Majority Element II follow-up that extends the same idea to two candidates.
LeetCode 448 is the definitive interview test for index-as-a-hash-key thinking. Learn the O(n) time, O(1) space negation trick that eliminates the need for any extra data structure — and every follow-up question a FAANG interviewer will throw at you after you solve it.
Given a binary array and an integer k, find the longest run of 1s you can create by flipping at most k zeros. Master the variable sliding window pattern that solves this in O(n) time and O(1) space — and learn the follow-up questions Google and Meta actually ask after you get it right.
Master LeetCode 414 — Third Maximum Number. Learn the subtle INT_MIN sentinel trap, two clean approaches (sorted set + three-variable O(1)), and real FAANG follow-up questions interviewers ask after you solve it.
Most shuffle implementations are silently biased. Learn why naive random fails, how Fisher-Yates guarantees every permutation is equally probable, and what FAANG interviewers really want to hear when they ask this question.
LeetCode 1480 is the gateway to one of the most powerful patterns in competitive programming and FAANG interviews: prefix sums. Master the in-place O(1) space solution, understand why the prefix sum array unlocks O(1) range queries, and learn the real follow-up questions — range sum queries, subarray sum equals K, and 2D matrix prefix sums — that interviewers ask once you solve this problem in thirty seconds.
Learn why 3Sum is a FAANG interview staple — how sorting enables two pointers, why deduplication trips up even strong candidates, a full visual dry run, and every common bug explained with Python and JavaScript solutions.
LeetCode 11 explained from scratch: why this is a greedy problem, the formal proof that you must always move the shorter pointer, a full step-by-step dry run, common traps, and clean Python + JavaScript solutions. Master the pointer-elimination pattern that appears throughout FAANG interviews.
LeetCode 238 is one of the most frequently asked medium problems at Google and Meta. Learn why the no-division constraint is intentional, how the prefix × suffix insight unlocks the O(n) solution, and how a single running variable eliminates the extra O(n) space entirely.
Master the classic Merge Intervals problem (LeetCode 56) asked at Google, Meta, Amazon, and Microsoft. Learn why sorting by start time is the key insight, the exact overlap condition (c ≤ b), a step-by-step visual dry run, 4 common mistakes, Python and JavaScript solutions, and follow-up problems including Insert Interval, Non-overlapping Intervals, and Meeting Rooms II.
Traverse an m×n matrix in spiral order. Master the boundary-shrinking technique — maintain top, bottom, left, right walls and peel layer by layer. Covers edge cases, visual dry run, common bugs, Python & JavaScript solutions, and follow-ups like Spiral Matrix II.
Group strings that are anagrams of each other using two canonical approaches: sorted string key O(n·k·log k) and character frequency tuple key O(n·k). Understand when the difference matters, trace through a dry run, dodge the common traps, and leave any interview with both solutions ready to go.
LeetCode 560 is one of the most-asked FAANG problems because it teaches the prefix sum + hashmap pattern — a technique that handles negative numbers, generalizes to a dozen follow-ups, and cannot be replaced by sliding window. Learn the insight, the dry run, the common mistakes, and the O(n) solution in Python and JavaScript.
LeetCode 33 is a rite of passage in FAANG interviews. Learn the one invariant that makes O(log n) possible on a rotated array, trace through a dry run, avoid the 4 most common bugs, and master the full family of follow-up problems (LC 81, LC 153, LC 154).
LeetCode 55 is a classic FAANG greedy problem that tests whether you can compress O(n²) DP thinking into a single O(n) pass. Learn the "max reachable index" insight, why greedy beats DP here, a full visual dry run, common traps, and every follow-up question interviewers ask next.
LeetCode 189 looks trivial — until the interviewer asks for O(1) space. Learn why three distinct approaches exist, the mathematical reason triple-reverse works, every common pitfall (wrong k, direction confusion, off-by-one), a full visual dry run, and how this trick unlocks Rotate String, Rotate Image, and beyond.
LeetCode 153 is one of the cleanest illustrations of binary search on a non-standard search space. Learn the rotation insight that unlocks O(log n), trace through a full visual dry run, avoid the three mistakes that most often break this one, and walk away ready for the duplicates variant (LC 154) and the full search-in-rotated problem (LC 33).
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.
LeetCode 152 looks like a simple extension of Maximum Sum Subarray — until you hit negative numbers. A negative times a negative is positive, which means the current minimum can instantly become the new maximum. Learn why tracking BOTH cur_max and cur_min is the essential insight, how zeros act as hard resets, the four bugs every candidate makes, and step-by-step dry runs on key examples. Python and JavaScript solutions from O(n²) brute force to the elegant O(n) DP approach.
Learn how to rotate an n×n matrix 90° clockwise in-place using the elegant transpose-then-reverse trick. Understand the math behind it, see the 4-cell direct rotation alternative, dry-run through a worked example, avoid the four most common mistakes, and get clean Python + JavaScript solutions.
Next Permutation is not just an array problem — it is a test of systematic algorithmic thinking under pressure. Learn why you scan from the right, why you swap with the smallest larger element, and why the suffix is reversed rather than sorted. Includes full visual dry runs, the 4 most common bugs, and Python + JavaScript solutions.
LeetCode 287 eliminates every naive approach through three hard constraints: no array modification, O(1) space, O(n) time. The solution — treating the array as an implicit linked list and running Floyd's tortoise-and-hare cycle detection — is one of the most elegant algorithm mappings in all of DSA. Full proof, visual dry run, Python and JavaScript solutions.
Master Dijkstra's Dutch National Flag algorithm to sort 0s, 1s, and 2s in a single pass with O(1) space. Understand the three-pointer invariants, the critical bug most candidates make, and how this pattern unlocks a family of partition problems.
Master LeetCode 57 with the three-phase sweep algorithm. Learn exactly how to insert and merge intervals in O(n) time — a pattern that appears repeatedly at Google, Amazon, and Meta.
Master LeetCode 435 with the greedy earliest-end-time strategy. Learn why sorting by end time is the key insight, walk through a visual dry run, and ace every FAANG follow-up on interval scheduling.
Master LeetCode 39 — Combination Sum by understanding the backtracking decision tree, why unlimited reuse is handled by staying at the same index, and how sorting enables early pruning. Includes Python and JavaScript solutions with line-by-line comments, a full visual dry run, common mistakes, and follow-up questions on LC 40, LC 216, and LC 377.
LC 46 — Permutations is the canonical backtracking problem every interviewer uses to test recursive thinking. Learn two clean approaches — the visited-array method and the in-place swap method — with a full decision-tree dry run for [1,2,3], the three most common interview mistakes, and real follow-up questions on LC 47 and LC 60.
LC 78 is the gateway to every combination and permutation problem in FAANG interviews. Master all three approaches — backtracking, bitmask enumeration, and iterative cascading — with deep visual dry runs, real interview follow-ups, and line-by-line Python and JavaScript solutions.
Master LeetCode 209 from first principles: understand why a variable-size shrinkable sliding window is the insight that cracks this problem in O(n), trace through every pointer movement on a real example, learn the three common interview mistakes, and be ready for the O(n log n) binary search follow-up that Amazon and Microsoft love to ask.
Master LeetCode 76 — the gold-standard Hard sliding window problem asked at Google, Meta, and Amazon. Learn the "formed" counter trick that reduces window validity checks from O(|t|) to O(1), trace through a full dry run, and avoid the five bugs that most often break this one.
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.
Master LeetCode 85 — Maximal Rectangle by building on LC 84 Largest Rectangle in Histogram. Learn the row-as-histogram insight, a visual row-by-row dry run, common pitfalls, and clean Python + JavaScript solutions that interviewers love.
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 410: learn why binary searching on the answer (not the array) is the key insight, walk through a full greedy feasibility check, and see both the DP and binary search solutions with line-by-line commentary.
Negative numbers completely break the classic sliding window for minimum-length subarray problems. Learn exactly why, then master the only correct approach — a monotonic deque on prefix sums — with a step-by-step visual trace, the three mistakes every candidate makes, and every real interview follow-up with approach hints.
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.
Master LeetCode 689 with a full visual dry run, left/right DP insight, Python and JavaScript solutions, and real interview follow-ups on generalizing to k windows.
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.
Master LeetCode 1493 with an intuition-first sliding window approach. Learn why you subtract 1 from the window size, trace through a real dry run, and ace every follow-up question an interviewer throws at you.
LeetCode 149 asks you to find the maximum number of collinear points on a 2D plane. The trick is representing slope as a GCD-reduced integer fraction — no floats, no precision bugs — and using a HashMap to count how many points share the same slope relative to each anchor. This post covers the full intuition, a step-by-step visual dry run, every edge case (vertical lines, duplicates, sign normalization), well-commented Python and JavaScript solutions, and the real FAANG follow-up questions that separate good candidates from great ones.
LeetCode 32 is one of the most deceptive Hard problems on the platform — the brute-force is obvious, but all three optimal solutions require genuinely different mental models. Master the index-sentinel stack, the DP recurrence, and the two-pass counter sweep, and you will be able to answer any follow-up a FAANG interviewer throws at you.
Most candidates jump straight to sorting. Learn the O(n) one-pass trick that finds the minimum and maximum of the violated region, expands the boundary correctly, and handles all edge cases — plus every FAANG follow-up interviewers actually ask.
Master LeetCode 795 using the elegant count(max <= R) - count(max <= L-1) subtraction trick — a powerful O(n) pattern that unlocks a whole family of subarray counting problems asked at Amazon, Google, and Meta.
LC 992 is one of the cleanest examples of a non-obvious reduction in competitive programming. Learn the "exactly K = atMost(K) minus atMost(K-1)" insight, trace through a full visual dry run, and understand how this single pattern unlocks five related hard problems in one shot.
LeetCode 1007 seems deceptively simple but hides a key insight that trips up most candidates: only the value on the very first domino can ever unify an entire row. Learn why this candidate-reduction observation collapses six potential targets into at most two, how to count rotations efficiently in a single pass, and what FAANG interviewers ask as follow-ups — including generalization to N faces and streaming domino inputs.
Master LC 936 Stamping the Sequence with reverse greedy simulation. Learn the core insight that working backwards transforms an impossible forward search into a tractable greedy problem. Python and JavaScript solutions with full commentary.
Week 1 of the FAANG mock interview program pairs easy and medium problems from arrays and trees. The goal is not ceiling testing — it is installing the think-aloud habits that distinguish passing candidates before difficulty ramps up in week 2.
LC 1151 asks for minimum swaps to group all 1s in a circular binary array. Count total 1s to set the window size, then maximize 1s inside any window position using modulo indexing. O(n) time, O(1) space.
LC 1052 maximizes satisfied customers by finding the optimal k-minute grumpiness suppression window. Decompose into a fixed base plus a variable bonus — then find the max-bonus window with a standard fixed-size sliding window. O(n) time, O(1) space.
Find the longest contiguous subarray of 1s after deleting exactly one element. Reframe as "longest window with at most one zero," then subtract 1 for the mandatory deletion. A clean shrinkable window problem.
Sort an array of 0s, 1s, and 2s in one pass with no extra space using the Dutch National Flag algorithm. Three pointers maintain sorted invariants for all three partitions simultaneously.
Check whether an integer array can be split into three contiguous parts with equal sum. LeetCode 1013 in O(n) using a greedy single-pass counter, with full Python and JavaScript code.
Master every JavaScript array method: map, filter, reduce, find, flat, flatMap, at, toSorted, and more. Real-world examples with TypeScript types to transform messy loops into clean, readable code.