131 articles
Ace behavioral interviews in 2026 with the STAR method, Amazon Leadership Principles deep dive, 50 common behavioral questions with answer frameworks, and how to prepare your story bank for any situation.
Two Sum is the #1 most-asked interview problem at Google, Amazon, and Meta — confirmed in over 170 interviews at 70 companies. But it is not about the solution. It is about showing you can trade space for time, recognize the hashmap complement pattern, and handle every follow-up a senior engineer can throw at you.
Learn why LeetCode 121 is a FAANG staple — not because it is hard, but because of what it reveals about your thinking. Master the running-minimum insight, avoid the global min/max trap, and understand all five stock variants from 121 to 309.
LC 217 looks trivially easy — but FAANG interviewers use it to probe your hashset vs sorting instincts, your ability to articulate space-time trade-offs, and whether you can spot the follow-up traps in LC 219 and LC 220. Full solutions in Python and JavaScript with deep explanation.
Most explanations of Kadane's Algorithm get it subtly wrong. Learn the correct mental model, the critical reset-to-0 bug that trips everyone up, a full visual dry run, divide-and-conquer alternative, and every FAANG follow-up question with approach hints.
LeetCode 283 is the gateway to the two-pointer partition pattern used across dozens of harder problems. Learn why it appears in almost every Microsoft and Amazon phone screen, master the write-pointer mental model with a step-by-step dry run, and understand when to swap vs. overwrite — with Python and JavaScript solutions fully annotated.
LeetCode 66 looks trivial until you hit [9,9,9]. Learn why interviewers love this problem, how carry propagation cascades through digits, the critical all-9s edge case that requires a new array, and why early termination makes your solution elegant — with Python and JavaScript solutions fully explained.
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 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).
Find the index of the first non-repeating character in a string. Two-pass O(n) solution with a 26-array or HashMap.
Count the number of prime numbers strictly less than n. Master the Sieve of Eratosthenes — one of the most elegant algorithms in CS — with full code in C, C++, Java, JavaScript and Python.
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.
Design a class to find the kth largest element in a data stream. Min-heap of size k: the top is always the answer. Full C++, Java, JavaScript and Python.
Compute running (prefix) sum in O(n) time O(1) extra space. The prefix sum pattern is foundational for range queries, subarray problems and 2D matrices.
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.
Master LeetCode 3 — the canonical sliding window problem. Understand the "shrink from left" insight, the critical stale-index bug with max(), and both set-based and hashmap-optimized solutions in Python and JavaScript. Includes a full step-by-step dry run and follow-up problems LC 340 and LC 159.
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 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.
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.
Insert a new interval into a sorted non-overlapping list and merge any overlaps in a single sweep.
Find all unique combinations that sum to a target, using backtracking with candidate reuse allowed.
Generate the power set of distinct integers using backtracking or bitmask enumeration.
Find the smallest contiguous subarray with sum >= target using the shrinkable sliding window technique.
Find all integers that appear twice using index-sign-marking trick in O(n) time and O(1) extra space.
Decode a run-length-encoded string like "3[a2[bc]]" = "abcbcabcbcabcbc" using a stack for nested brackets.
Find all unique combinations that sum to target where each number may be used once, skipping duplicates at each recursion level.
Search for a word in a 2D grid using DFS backtracking with in-place visited marking.
Determine if there exists an increasing subsequence of length 3 using two greedy variables in O(n) time O(1) space.
Find all unique quadruplets summing to target by extending the 3Sum pattern with an outer loop and duplicate skipping.
Find minimum number of jumps to reach the last index using greedy BFS-style level tracking.
Determine the unique starting gas station for a circular route using a greedy one-pass algorithm.
LeetCode 739 — Find the number of days until a warmer temperature for each day using a monotonic decreasing stack. The key insight: store indices, not temperatures, in the stack. When a warmer day arrives, it is the "next greater element" for every cooler day still waiting on the stack — a fundamental pattern that appears in at least six other LeetCode problems.
LeetCode 128 — Find the longest consecutive integer sequence in O(n) using a HashSet. The trick: only start counting from numbers where num-1 is NOT in the set, so each element is visited at most twice total across the entire algorithm.
Partition a string into the maximum number of parts where each letter appears in at most one part, using last occurrence mapping.
Calculate minimum CPU intervals for tasks with cooldown using a greedy formula based on the most frequent task count.
Find the minimum arrows needed to burst all balloons arranged as intervals using a greedy sort-by-end approach.
Find the missing number in [0..n] using the Gauss sum formula or XOR in O(n) time O(1) space.
Find all elements appearing more than n/3 times using Extended Boyer-Moore Voting with two candidate trackers.
Compress a sorted unique integer array into the smallest sorted list of range coverage strings.
Distribute minimum candies so each child with higher rating than neighbors gets more, using left-to-right then right-to-left passes.
Find the minimum total moves to make all array elements equal by targeting the median value.
Find the longest nested set S(k) in a permutation array by tracing cycles with visited marking in O(n) time.
Generate all unique subsets from an array with duplicates by sorting and skipping repeated elements at each recursion level.
Check if string B is a rotation of A by checking if B appears in A+A using a substring search.
LeetCode 42 is a benchmark Hard problem used by Amazon, Google, and Meta to test whether you can derive an insight — not just memorize code. Learn all three approaches (brute force, prefix arrays, two pointers) and — crucially — understand WHY the two-pointer invariant works.
Most candidates brute-force this in O(n·k) and hit TLE. Learn the monotonic deque invariant that reduces it to O(n) — with a step-by-step dry run, the five common bugs that break implementations, and why this pattern unlocks Jump Game VI and Constrained Subsequence Sum.
LeetCode 41 is a landmark Hard problem because both obvious approaches — hash set and sorting — are explicitly banned by the constraints. Learn the mathematical insight that bounds the answer to [1, n+1], then master two O(n) time, O(1) space techniques: index marking via sign negation and cyclic sort placement, with a full visual dry run, bug catalogue, and FAANG follow-ups.
Master LeetCode 84 the right way. Learn exactly why bars are popped from the monotonic stack, how to calculate left/right boundaries without bugs, the sentinel-values trick that eliminates edge cases, and a step-by-step dry run on [2,1,5,6,2,3] — plus how this pattern extends directly to Maximal Rectangle (LC 85).
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 trip up 90% of candidates.
Count elements smaller than each element to its right using a modified merge sort that counts inversions during the merge step.
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.
Find the largest rectangle of 1s in a binary matrix by treating each row as a histogram and applying the Largest Rectangle in Histogram algorithm.
Count pairs (i,j) where i<j and nums[i]>2*nums[j] using modified merge sort to count cross-half pairs before merging.
Minimize the largest sum among m subarrays by binary searching on the answer and greedy checking feasibility.
Find the shortest subarray with sum >= K using a monotonic deque on prefix sums, handling negative numbers correctly.
Find the minimum refueling stops to reach target by greedily picking the largest fuel station passed so far whenever we run out.
Find the longest subarray of 1s after deleting exactly one element using a sliding window that tracks the count of zeros.
Find the maximum number of points on the same line using a slope-as-fraction HashMap for each anchor point.
Find the longest valid parentheses substring using a stack that tracks the last unmatched index as a base.
Find the shortest subarray that when sorted makes the whole array sorted, using a single linear scan tracking violated boundaries.
Count subarrays where max element is in [L,R] using a clever counting formula with two linear scans.
Count subarrays with exactly K distinct integers using the formula: atMost(K) - atMost(K-1).
Find the minimum rotations to make all tops or bottoms equal by checking if a target value (from first domino) can unify the entire row.
Find the longest substring that appears at least twice using binary search on length and Rabin-Karp rolling hash for O(n log n) average time.
Design a stack that pops the most frequent element (breaking ties by recency) using frequency and group-stacks mapping.
Find two indices that add to target in O(n) by storing each number in a HashMap and looking up the complement.
Check if two strings are anagrams by comparing their character frequency counts using an array or HashMap.
Check if a ransom note can be constructed from magazine letters using a character frequency map.
Check if two strings are isomorphic by maintaining bidirectional character mappings to ensure a consistent one-to-one correspondence.
Check if a string follows a given pattern using bidirectional mapping between pattern chars and words.
Determine if a number is happy by repeatedly summing digit squares and detecting cycles using a HashSet or Floyd algorithm.
Count how many stones are jewels by storing jewel types in a HashSet and checking each stone.
Group strings that are anagrams together by using their sorted form as a HashMap key.
Find the k most frequent elements in O(n) using bucket sort by frequency instead of a heap.
Design a Least Recently Used cache with O(1) get and put operations using a HashMap combined with a doubly linked list.
Count subarrays with sum exactly k using prefix sums stored in a HashMap to find valid starting positions in O(n).
Check if a continuous subarray of length >= 2 sums to a multiple of k using prefix sum modulo k with a HashMap.
Find the longest consecutive integer sequence in O(n) by using a HashSet and only starting sequences from their minimum element.
Design a set with O(1) insert, delete, and getRandom using a dynamic array combined with a HashMap for index tracking.
Find all starting indices of anagram substrings by using a fixed window with character frequency comparison.
Implement weighted random selection by building a prefix sum array and using binary search to find the sampled index.
Find the vertical line that crosses the fewest bricks by counting the most frequent gap position using a HashMap.
Remove all occurrences of val in-place using a write pointer pattern, returning the new length.
Merge two sorted arrays in-place from the end to avoid overwriting elements using three pointers.
Check if string s is a subsequence of t using a greedy two-pointer scan that matches characters in order.
Compute the running sum of a 1D array where each element is the sum of itself and all previous elements.
Find the longest substring without duplicate characters using a HashSet-backed shrinkable sliding window.
Check if any permutation of s1 is a substring of s2 using a fixed-size sliding window with character frequency comparison.
Find the smallest subarray with sum >= target using a variable sliding window that shrinks from the left when the condition is met.
Maximize water trapped between two vertical lines using inward two pointers that always move the shorter line inward.
Find minimum boats to save everyone where each boat carries at most 2 people with total weight <= limit, using sort + greedy two pointers.
Find all unique triplets summing to zero by sorting and using two pointers for each fixed element with careful duplicate skipping.
Find two numbers summing to target in a 1-indexed sorted array using inward two pointers in O(n) time O(1) space.
Maximize card points taken from both ends of an array by finding the minimum-sum subarray of size n-k in the middle.
Find minimum operations to reduce X to zero from either end by finding the longest middle subarray with sum = total-X.
Find the maximum number of vowels in any substring of length k using a fixed sliding window with vowel count.
Find minimum swaps to group all 1s together in a circular binary array using a fixed-size sliding window equal to the count of 1s.
Maximize customer satisfaction by finding the best k-minute window for the bookstore owner to stay non-grumpy.
Count substrings containing at least one a, b, and c using the last-seen indices shortcut for O(n) time.
Count subarrays with sum divisible by k using prefix sum modulo k and a frequency map of remainders.
Sort only the vowels in a string while keeping consonants in place by extracting vowels, sorting, then reinserting.
Find the median of each sliding window of size k using two heaps (max-heap for lower half, min-heap for upper half) with lazy deletion.
Find the smallest window in s containing all characters of t using a have/need counter to track when the window is valid.
Find the maximum in every sliding window of size k in O(n) using a monotonic decreasing deque of indices.
Find the shortest subarray with sum >= k, handling negative numbers correctly using a monotonic deque on prefix sums.
Check if a string can become a palindrome by deleting at most one character using recursive two-pointer palindrome checking.
Calculate trapped rainwater using optimal two-pointer approach that tracks left and right maximums without extra space.
Full company-specific mock sessions. Each simulation replicates the actual interview format, problem difficulty distribution, and evaluation criteria of Google, Meta, and Amazon.
Map Amazon's 16 Leadership Principles to coding interview behaviors. Know which LP each behavioral question targets, and how to weave LP language naturally into technical answers.
Strategic guide to company-specific DSA preparation: Google's focus on graphs and DP, Meta's emphasis on arrays and trees, Amazon's leadership principles alignment with system design and BFS.
Count islands after each addLand operation using incremental Union-Find. Each new land cell potentially merges with up to 4 neighbors — classic Amazon system-at-scale problem.
Design a stream that always returns the kth largest element after each add. Uses a min-heap of size k — the top is always the kth largest.
Find the minimum intervals to complete all tasks given cooldown n. Greedy with max-heap: always execute most frequent available task, idle only when forced.
Merge k sorted linked lists into one sorted list using a min-heap. O(n log k) time by always extracting the current minimum across all list heads.
Find the k most frequent elements using a max-heap or bucket sort. O(n) bucket sort approach using frequency as bucket index — faster than O(n log n) heap.
Comprehensive coverage of Two Sum, Two Sum II (sorted), 3Sum, and 4Sum. Amazon frequently tests these variants to gauge understanding of hashmap vs two-pointer trade-offs.
Find the median of two sorted arrays in O(log(min(m,n))) time using binary search on partition points. A classic hard problem testing deep binary search understanding.
Complete recap of all 24 company-tagged problems with pattern classification, company attribution, and key insights. Use as a final review checklist before company-specific interviews.