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Medium3Sum — Sort Then Two-Pointer Search
Sort the array, fix one value, and sweep the remaining window with two pointers while skipping duplicates.
Two PointersSortingArray
Articles
Short articles that give you the key insights and takeaways from popular coding problems.
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HardAlien Dictionary — Topological Sort on Characters
Compare adjacent words to derive ordering constraints between letters, then perform Kahn’s algorithm.
GraphTopological SortString
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EasyBest Time to Buy and Sell Stock — Track a Running Minimum
Capture the lowest buying price so far and measure profit deltas in a single scan.
ArrayDynamic ProgrammingGreedy
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MediumBinary Tree Level Order Traversal — BFS by Levels
Use a queue to traverse nodes level by level, collecting values into lists per depth.
TreeBFS
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HardBinary Tree Maximum Path Sum — DFS with Returning Branch Gains
Compute the best downward gain from each node while tracking the maximum path that can pass through the node.
TreeDFS
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EasyClimbing Stairs — Fibonacci DP
Reuse the recurrence f(n) = f(n-1) + f(n-2) with constant space to count distinct stair-climbing ways.
Dynamic Programming
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MediumCoin Change — Bottom-Up Dynamic Programming
Build the minimum coins needed for each amount up to target using previously computed states.
Dynamic Programming
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MediumCombination Sum — Backtracking with Reuse
Perform depth-first search, deciding how many times to pick each candidate while keeping the combination in non-decreasing order.
BacktrackingDFS
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MediumContainer With Most Water — Two-Pointer Contraction
Hold both ends of the array and always move the shorter wall inward to maximise trapped area in one pass.
Two PointersArrayGreedy
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EasyContains Duplicate — Hash Set Membership
Track seen numbers in a set; if a value appears twice, return true immediately.
Hash SetArray
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EasyCounting Bits — DP from Lowest Set Bit
Use the recurrence dp[i] = dp[i >> 1] + (i & 1) to build popcounts from 0 to n.
Dynamic ProgrammingBit Manipulation
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MediumCourse Schedule — Topological Sort with Cycle Detection
Use Kahn’s algorithm (BFS) or DFS to detect cycles in the prerequisite graph and decide feasibility.
GraphTopological Sort
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MediumDecode Ways — DP Over Digits
Use dp[i] representing ways to decode the prefix up to i by considering one or two-digit translations.
Dynamic ProgrammingString
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MediumFind Minimum in Rotated Sorted Array — Binary Search on Sorted Halves
Use binary search to locate the pivot: if the mid element is greater than the rightmost element, search the right half; otherwise search the left.
Binary SearchArray
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MediumGraph Valid Tree — Union Find Cycle Check
Treat the graph as a disjoint set; every edge must connect two different components and the graph needs exactly n − 1 edges.
GraphUnion FindBreadth-First Search
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MediumGroup Anagrams — Canonical Signature Hashing
Use a canonical key (sorted string or frequency vector) to bucket anagrams together in linearithmic time overall.
Hash MapString
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MediumHouse Robber — Linear DP with Two Choices
At each house decide whether to rob it by comparing robbing plus skipping previous versus skipping now.
Dynamic Programming
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MediumImplement Trie — Prefix Tree Operations
Build a node structure with child maps and an isWord flag to support insert, search, and prefix queries in O(L).
TriePrefix Tree
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MediumInsert Interval — Merge While Inserting
Walk the sorted intervals, append those ending before the new interval, merge overlaps, then append the rest.
IntervalGreedy
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EasyInvert Binary Tree — Recursive Swap
Swap left and right children at every node using recursion or BFS to mirror the tree.
TreeBFS
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MediumJump Game — Greedy Furthest Reach
Track the furthest index reachable so far; if you ever fall behind the current index, the end cannot be reached.
GreedyArray
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EasyLinked List Cycle — Floyd’s Tortoise and Hare
Run two pointers at different speeds; if a cycle exists they eventually collide without any extra memory.
Linked ListTwo PointersCycle Detection
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MediumLongest Palindromic Substring — Expand Around Center
Treat every character and gap as a center, expanding while the ends mirror each other to find the best span.
Two PointersExpand Around CenterString
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MediumLongest Substring Without Repeating Characters — Sliding Window Map
Slide a window while remembering the last index of each character so duplicates never stay in view.
Sliding WindowHash MapString
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EasyLowest Common Ancestor in BST — Guided Descent
Leverage BST ordering: move left or right until the current node splits the two targets.
TreeBinary Search Tree
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EasyMaximum Depth of Binary Tree — DFS Height Calculation
Return 1 plus the maximum depth of left and right subtrees using recursion.
TreeDFS
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MediumMaximum Product Subarray — Track Hi/Lo Products
Maintain both the highest and lowest running product because negative numbers can flip the sign of the result.
Dynamic ProgrammingArray
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MediumMaximum Subarray — Kadane’s Running Sum
Carry a running best prefix; reset when it becomes negative so the subarray that follows starts fresh.
Dynamic ProgrammingArray
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EasyMeeting Rooms — Sort and Check Overlaps
Sort intervals by start time and ensure each meeting starts after the previous one ends.
IntervalSorting
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MediumMeeting Rooms II — Sweep Line on Start/End Times
Separate start and end times, sort both, and sweep to find the maximum number of concurrent meetings.
IntervalHeap
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MediumMerge Intervals — Sort Then Sweep
Sort intervals by start time and greedily merge overlapping ranges with a running tail pointer.
IntervalSorting
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HardMerge k Sorted Lists — Min-Heap Merge
Push the head of each list into a min-heap and repeatedly extract the smallest node to build the merged list.
HeapLinked ListDivide and Conquer
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EasyMerge Two Sorted Lists — Dummy Head Merge
Use a dummy head and advance two pointers, always stitching the smaller node into the merged list.
Linked ListTwo Pointers
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HardMinimum Window Substring — Sliding Window with Counts
Expand the window to satisfy the requirement, then shrink from the left to find the smallest valid window.
Sliding WindowHash Map
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EasyMissing Number — Arithmetic Series Difference
Compute the expected sum of 0..n and subtract the observed sum to recover the missing value in constant space.
MathArray
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EasyNumber of 1 Bits — Brian Kernighan’s Trick
Clear the lowest set bit repeatedly by applying n & (n - 1) until the number becomes zero.
Bit Manipulation
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MediumNumber of Connected Components — Union-Find Tracking
Initialise each node in its own set and union edges; the remaining number of roots equals the connected components.
Union FindGraph
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MediumNumber of Islands — DFS Flood Fill
Treat the grid as a graph; whenever you encounter land, run DFS/BFS to sink the entire island and increment the count.
DFSBFSGrid
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MediumPalindromic Substrings — Count by Expanding Centers
Expand around every index and gap to count palindromic substrings without building a DP table.
Expand Around CenterStringCounting
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MediumProduct of Array Except Self — Prefix and Suffix Multiplication
Compute prefix products and suffix products to fill the output without division.
Array
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MediumRemove Nth Node From End — One-Pass Two Pointers
Advance a front pointer n steps ahead so that when it hits null, the trailing pointer sits right before the node to remove.
Linked ListTwo Pointers
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MediumReorder List — Split, Reverse, Merge
Break the list in half, reverse the back half, and weave the two lists together to match L0, Ln, L1, Ln-1 ... order.
Linked ListTwo Pointers
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EasyReverse Bits — Bitwise Swapping
Swap symmetric bit pairs by shifting and masking until you have reversed the 32-bit integer.
Bit Manipulation
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EasyReverse Linked List — Iterative Pointer Reversal
Walk the list once while rewiring next pointers to build the reversed list in-place.
Linked List
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MediumRotate Image — Layered Matrix Transpose and Reverse
Transpose the square matrix then reverse each row to achieve an in-place 90° rotation.
MatrixIn-Place
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EasySame Tree — Parallel DFS Comparison
Traverse both trees simultaneously; if nodes mismatch in structure or value, return false.
TreeDFS
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MediumSearch in Rotated Sorted Array — Pivot-Aware Binary Search
Decide which side of the pivot is sorted at every step so the binary search converges on the target in logarithmic time.
Binary SearchArray
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MediumSet Matrix Zeroes — Mark First Row and Column
Use the first row and column as markers to remember which rows and columns should be zeroed without extra space.
Matrix
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MediumSpiral Matrix — Layer-by-Layer Traversal
Maintain four boundaries (top, bottom, left, right) and peel layers while updating them carefully.
MatrixSimulation
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EasySubtree of Another Tree — Serialize or DFS Compare
Either serialise both trees and search for the subtree pattern or perform depth-first node comparisons with early pruning.
TreeDFS
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MediumSum of Two Integers — Bitwise Addition
Use XOR for partial sums and AND/shift for carries until no carry remains.
Bit Manipulation
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MediumTop K Frequent Elements — Bucket or Heap
Count element frequencies with a hash map and extract the top k using either a min-heap or frequency buckets.
HeapHash Map
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EasyTwo Sum — One-Pass Hash Map
Eliminate the quadratic brute force by caching complements as you sweep the array once.
ArrayHash MapComplement Search
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MediumUnique Paths — Grid Dynamic Programming
Count paths from top-left to bottom-right by summing ways from the top and left neighbors.
Dynamic ProgrammingGrid
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EasyValid Anagram — Frequency Comparison
Count character frequencies in both strings and ensure the counts match exactly.
Hash MapString
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EasyValid Palindrome — Two-Pointer Scan Ignoring Non-Alphanumerics
Move pointers inward while skipping non-alphanumeric characters; compare lowercased characters for equality.
Two PointersString
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EasyValid Parentheses — Stack-Based Matching
Push opening brackets onto a stack and ensure every closing bracket matches the most recent opener.
StackString
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MediumWord Break — BFS Over Split Positions
Treat indices as graph nodes and BFS through valid dictionary cuts to decide whether the entire string can be segmented.
Dynamic ProgrammingBreadth-First SearchString
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MediumWord Search — Backtracking on a Grid
Perform DFS from each cell, marking visited cells temporarily to avoid reuse within the same path.
BacktrackingGrid
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HardWord Search II — Trie-Guided Backtracking
Insert all words into a trie and prune DFS paths that are not prefixes, collecting matches as you traverse.
TrieBacktrackingGrid
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IntermediateBacktracking Fundamentals — Exploring All Possibilities
Master the backtracking pattern by learning when to explore paths, how to prune invalid branches, and why state management is critical.
BacktrackingRecursionDFS
Deep-dive guide
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FoundationBinary Search — Shrinking Search Space with Confidence
Internalise the binary search loop so you can apply it to sorted arrays, answer-range problems, and monotonic predicates.
Binary SearchArraysAlgorithm
Deep-dive guide
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FoundationBreadth-First Search — Level Order Thinking
Learn how BFS explores graphs layer by layer, powers shortest unweighted paths, and pairs perfectly with queues.
BFSGraphsTraversal
Deep-dive guide
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IntermediateBuilding a Trie from Scratch
Construct a prefix tree that supports insert and search in O(L), and learn how to extend it for autocomplete prompts.
TriePrefix Tree
Deep-dive guide
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FoundationDepth-First Search — Recursive and Iterative Patterns
Understand DFS as a flexible template for exploring as far as possible, powering cycle detection, connected components, and backtracking.
DFSGraphsRecursion
Deep-dive guide
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IntermediateDijkstra’s Algorithm — Weighted Shortest Paths
Move beyond unweighted graphs by mastering Dijkstra’s priority-queue based approach to shortest paths with non-negative weights.
DijkstraGraphsShortest Path
Deep-dive guide
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FoundationGraph Representation Toolkit — Modeling Real Problems
Translate interviews into graph problems by choosing the right representation: adjacency lists, matrices, edge lists, and implicit neighbors.
GraphsData Modeling
Deep-dive guide
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FoundationHeaps & Priority Queues — Controlling Extremes Fast
Learn how heaps provide O(log n) insertions and removals for extreme values, powering top-K, scheduling, and streaming problems.
HeapPriority QueueData Structure
Deep-dive guide
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EasyInterview Flowchart — A 20-Minute Diagnostic
Turn the Interview Flowchart into a repeatable script: clarify, pattern match, and choose the right tool without freezing mid-round.
Interview StrategyProblem SolvingFlowchart
Deep-dive guide
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FoundationKadane’s Pattern — Linear-Time Maximum Subarray
Use Kadane’s dynamic programming insight to find maximum subarray sums, track boundaries, and pivot to 2D variations.
Dynamic ProgrammingKadaneArrays
Deep-dive guide
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FoundationLinked List Fundamentals — Pointers with Purpose
Demystify singly and doubly linked lists, pointer manipulation, and fast/slow patterns that dominate interview questions.
Linked ListPointers
Deep-dive guide
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FoundationMastering Hash Maps in Interview Settings
Learn how to recognise hash map opportunities, pick collision strategies, and explain amortised behaviour with confidence.
Hash MapData Structure
Deep-dive guide
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IntermediatePattern Searching in Strings — Sliding Windows & Prefixes
Master core string search techniques: naive sliding window, Rabin-Karp hashing, and prefix-function-based KMP.
StringsPattern Searching
Deep-dive guide
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FoundationQueue Patterns — First-In, First-Out Workflows
Learn how queues model real-world workflows, feed BFS, and support monotonic optimisations like sliding window maximum.
QueueData Structure
Deep-dive guide
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FoundationSorting Strategies — Choosing the Right Order
Compare sorting algorithms, understand when to reach for mergesort vs. quicksort, and explain stability, in-place trade-offs, and custom comparators.
SortingAlgorithm
Deep-dive guide
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IntermediateTopological Sort — Ordering with Dependencies
Learn how to order tasks with prerequisites using Kahn’s algorithm or DFS post-order, and recognise when topological sort applies.
Topological SortGraphsDAG
Deep-dive guide