45 articles
Learn how to find the next greater node in a linked list using a monotonic stack in O(n) time. A popular interview question at Amazon and Adobe that tests your stack intuition and linked list traversal skills.
A deep-dive into implementing a linked list from scratch — a classic data structures interview question at Amazon, Google, and Microsoft that tests your true understanding of pointers, node management, and edge case handling.
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.
Learn how to remove consecutive nodes that sum to zero from a linked list using a prefix sum hashmap in two passes. A tricky interview problem asked at Google and Amazon that combines linked list manipulation with the classic prefix sum technique.
Learn how to split a linked list into k roughly equal parts in O(n) time using integer division and remainder math. A clean medium interview problem asked at Amazon and Facebook that tests linked list traversal and arithmetic reasoning.
Master reversing a subrange of a linked list in-place in a single pass. A classic interview problem at Facebook, Microsoft, and Amazon that tests your pointer manipulation skills and ability to handle complex multi-pointer state.
Find the maximum twin sum of a linked list in O(n) time and O(1) space by reversing the second half and comparing node pairs. A modern LeetCode 75 problem asked at Amazon and Google that combines fast-slow pointers with in-place list reversal.
Learn how to merge all nodes between consecutive zeros in a linked list into a single sum node in O(n) time and O(1) space. A clean simulation problem from LeetCode 2181 that tests in-place pointer manipulation and linked list traversal confidence.
Learn how to delete the middle node of a linked list in one pass using a clever modification of the fast/slow pointer technique. A LeetCode 75 problem asked at Amazon and Google that tests your understanding of the tortoise-and-hare algorithm.
Learn how to reverse nodes in each even-length group of a linked list by carefully counting group sizes and applying in-place reversal. A moderately tricky interview problem at Amazon and Google that tests group traversal and selective reversal skills.
Master the three cases needed to insert a value into a sorted circular linked list correctly. A classic interview problem at Google, Facebook, and Amazon that tests your ability to handle circular structure edge cases and write bug-free pointer manipulation code.
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.
Learn three ways to flatten a binary tree to a pre-order linked list in-place, including the O(1) space Morris-style approach. A classic interview problem at Microsoft, Amazon, and Google that bridges tree and linked list manipulation.
Convert a sorted linked list to a height-balanced binary search tree using fast/slow pointers to find the midpoint recursively. A classic divide-and-conquer interview problem at Amazon, Google, and Microsoft that bridges linked list and BST skills.
Master reversing nodes in groups of k in a linked list — the classic hard interview problem asked at Amazon, Google, Facebook, and Microsoft. Learn both the elegant recursive solution and the iterative approach with clear pointer diagrams.
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 bottom-up merge sort on a linked list for O(n log n) time and O(1) space — eliminating the O(log n) recursive stack. A hard interview problem at Amazon, Google, and Facebook that demonstrates deep understanding of merge sort and linked list mechanics.
Learn the optimal O(n) approach to convert a sorted linked list to a height-balanced BST using in-order construction — consuming list nodes sequentially without finding the midpoint each time. A clever interview technique at Amazon, Google, and Microsoft that demonstrates advanced recursion thinking.
Build an LRU Cache from scratch using a doubly linked list with sentinel nodes and a HashMap for O(1) get and put operations. The most frequently asked hard design problem at Amazon, Microsoft, Google, and Facebook — explained step by step with diagrams.
Implement a browser history data structure with visit, back, and forward operations using a doubly linked list for O(1) navigation. A practical design interview problem at Amazon, Microsoft, and Google that tests your ability to model real-world state with linked list pointers.
A complete linked list interview playbook covering 7 core patterns (reversal, fast/slow, dummy head, merge, in-place, clone, design) with copy-paste templates and a curated index of 45 LeetCode problems mapped to every pattern.
LeetCode 206 Reverse Linked List is the foundational pointer-manipulation problem at FAANG interviews. Master the iterative three-pointer rewiring and the recursive call-stack reversal — both are used as subroutines in dozens of harder problems.
LeetCode 876 Middle of the Linked List teaches the fast/slow pointer technique that appears in half of all linked-list interview problems. Find the middle node in one pass with zero extra space, and understand exactly which middle you get for even-length lists.
LC 141 Linked List Cycle is a classic interview question asked by Amazon, Microsoft, and Google that tests your mastery of the two-pointer fast/slow technique. Learn Floyd's tortoise and hare algorithm with a visual dry run, Python and JavaScript solutions, and key interview tips.
LC 21 Merge Two Sorted Lists is one of the most frequently asked linked list interview problems at Amazon, Google, and Microsoft. Learn the dummy head merge pattern with step-by-step Python and JavaScript solutions, visual dry run, and interview tips.
LC 234 Palindrome Linked List is a popular interview problem at Facebook, Amazon, and Apple that combines three core techniques: fast/slow pointer midpoint finding, in-place list reversal, and two-pointer comparison. Master the O(1) space solution with Python and JavaScript code and a step-by-step dry run.
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 237 Delete Node in a Linked List is a clever trick problem asked at Adobe and Microsoft that tests whether you understand linked list node deletion when you only have access to the node itself and not the head. Learn the copy-and-skip approach with Python and JavaScript solutions.
LC 160 Intersection of Two Linked Lists is a popular O(1) space interview question at Amazon, Facebook, and Microsoft. Learn the elegant two-pointer length-equalizer trick, the mathematical proof behind why it works, visual dry run, and Python/JavaScript solutions.
LC 1290 Convert Binary Number in a Linked List to Integer is an easy interview problem that combines linked list traversal with binary number conversion. Learn the elegant bit-shift accumulation pattern with Python and JavaScript solutions, dry run, and interview tips.
LC 203 Remove Linked List Elements is a fundamental interview problem asked at Google and Amazon that teaches the dummy head sentinel pattern for handling head deletion cleanly. Learn O(n) solutions in Python and JavaScript with visual dry run, common mistakes, and recursive variant.
LC 19 Remove Nth Node From End of List is a classic one-pass interview problem at Amazon, Google, and Facebook that combines the dummy head sentinel with a two-pointer n-gap technique. Learn the optimal O(n) single-pass solution with Python and JavaScript, step-by-step dry run, and common interview traps.
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 328 Odd Even Linked List is a medium interview problem at Facebook, Amazon, and LinkedIn that tests your ability to maintain two separate pointer chains simultaneously. Learn the O(1) space two-chain pattern with Python and JavaScript, a visual dry run, and interview tips.
LC 61 Rotate List is a medium interview problem at Amazon and Microsoft that tests your ability to use circular linked list manipulation and modular arithmetic to rotate by k positions efficiently. Learn the optimal O(n) solution with Python and JavaScript, detailed dry run, and the critical k mod n insight.
LC 143 Reorder List is a composite interview problem at Facebook, Amazon, and Google that combines three core patterns: fast/slow midpoint finding, in-place second-half reversal, and interleaved merging. Master the O(1) space solution with Python and JavaScript, step-by-step visual trace, and interview approach.
LC 2 Add Two Numbers is one of the most iconic interview problems at Amazon, Google, and Microsoft where you simulate grade-school addition on two reversed linked lists digit by digit. Master the carry propagation technique with Python and JavaScript solutions, visual dry run, and common pitfalls.
LC 445 Add Two Numbers II is a medium interview problem at Amazon and Google where numbers are stored most-significant-digit first, requiring stacks or list reversal to process from LSB. Learn the optimal stack-based solution with Python and JavaScript, dry run, and the key difference from LC 2.
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 148 Sort List is a classic O(n log n) interview problem at Amazon, Google, and Facebook that applies merge sort to a linked list using fast/slow pointer splitting and recursive merging. Learn top-down merge sort with Python and JavaScript, a complete dry run, and the bottom-up O(1) space follow-up.
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.
LC 138 Copy List with Random Pointer is a medium interview problem at Amazon, Microsoft, and Facebook that requires deep-copying a linked list where each node has a random pointer. Learn the O(n) space hash map approach and the clever O(1) space interleave technique with Python and JavaScript solutions and detailed dry run.
LC 430 Flatten a Multilevel Doubly Linked List is a medium interview problem at Microsoft and Amazon that uses DFS or an explicit stack to inline child sub-lists into the main list. Learn the iterative stack approach and the recursive approach with Python and JavaScript, step-by-step dry run, and interview tips.
LC 142 Linked List Cycle II is a medium interview problem at Amazon, Microsoft, and Google where you find the exact node where a cycle begins using Floyd's algorithm and a mathematical proof. Learn the two-phase approach with Python and JavaScript, the math proof, visual dry run, and common interview questions.
LC 287 Find the Duplicate Number is a brilliant medium interview problem at Amazon, Google, and Facebook where you find a duplicate in an n+1 integer array in O(1) space by treating the array as an implicit linked list and applying Floyd's cycle detection algorithm. Master the connection between arrays and linked lists with Python and JavaScript solutions and detailed proof.