18 articles
Master swapping the kth node from start and end in a linked list using the two-pointer technique. A clean O(n) interview question asked at Amazon and Bloomberg that tests linked list traversal confidence and pointer discipline.
Count the number of connected components in a linked list defined by a given set of values using a single traversal and O(1) HashSet lookups. A clean O(n) interview problem at Google, Amazon, and Bloomberg that tests your ability to convert a graph concept into a simple linear scan.
LeetCode 547 Number of Provinces is the canonical connected-components question. Learn the DFS, BFS, and Union Find solutions, master the adjacency-matrix walk, and rehearse the FAANG interview script.
LeetCode 480 (Hard) — a Google and Bloomberg favorite. Compute the median of every k-sized window using two heaps with a lazy deletion hash map.
LC 83 Remove Duplicates from Sorted List is a foundational linked list interview problem asked at Bloomberg and Microsoft. Learn the single-pass pointer walk solution with Python and JavaScript, a visual dry run, common traps, and how to extend it to the harder variant (LC 82).
LC 24 Swap Nodes in Pairs is a medium linked list interview problem at Microsoft and Bloomberg that tests precise multi-step pointer manipulation. Learn the iterative dummy-head approach and the recursive solution with Python and JavaScript, detailed visual dry run, and interview tips.
LC 86 Partition List is a medium interview problem at Bloomberg and Amazon that extends the dummy-head two-chain pattern to partition by value comparison. Learn the stable O(n) solution with Python and JavaScript, visual dry run, and critical edge cases including the tail-cycle trap.
LC 82 Remove Duplicates from Sorted List II is a medium interview problem at Google, Amazon, and Bloomberg where you remove ALL nodes that appear more than once from a sorted list. Learn the dummy-head predecessor skip pattern with Python and JavaScript, step-by-step dry run, and the critical difference from LC 83.
Crack LeetCode 363 Max Sum of Rectangle No Larger Than K by fixing two row boundaries to collapse 2D into 1D, then using prefix sums plus a sorted set (or BIT/segment tree) to find the best subarray sum bounded above by K.
Design a stack that supports push, pop, top, and getMin in O(1) time using a parallel min-tracking stack. A classic FAANG design interview problem testing stack invariants and auxiliary state maintenance.
Calculate the stock price span using a monotonic decreasing stack that stores (price, span) pairs and accumulates spans in O(1) amortized time. A classic streaming design problem that tests span accumulation and the monotonic stack pattern.
Simulate asteroid collisions where right-moving asteroids accumulate on the stack and left-moving ones destroy smaller ones on collision. A clean application of the collision-simulation stack pattern asked at Amazon and Bloomberg.
Solve LeetCode 456 132 Pattern in O(n) using a monotonic stack scanned from right to left while tracking the best second-largest. A FAANG interview favorite at Bloomberg, Amazon, and Google.
LeetCode 101 — Symmetric Tree, asked at Amazon, Microsoft and Bloomberg. Compare opposite subtrees with a two-pointer recursive helper to check mirror symmetry in O(n) time.
LeetCode 96 Unique Binary Search Trees asks for the count of structurally unique BSTs storing 1..n. Solve it in O(n^2) using Catalan number DP — a favorite Amazon and Google interview question.
LeetCode 977 Squares of a Sorted Array is a classic Google and Bloomberg two pointer question. Squaring negatives flips the sort order, so we merge from the outside in to produce a sorted output in O(n) time without re-sorting.
LeetCode 88 Merge Sorted Array is the classic three pointer in-place merge problem at Microsoft, Bloomberg, and Amazon. Walk both arrays from the end into the trailing empty slots to achieve O(m plus n) time with O(1) extra space.
LeetCode 480 asked at Google, Amazon, and Bloomberg. Maintain a max-heap and a min-heap with lazy deletion to compute the median in O(n log k) time.