A simple pattern that turns O(N²) brute force solutions into O(N). Master the two pointer technique and recognize the problem types where it applies.
The data structure behind autocomplete, spell checkers, and IP routing. Learn how tries store strings efficiently and enable O(L) search regardless of how many words are stored.
The data structure behind file systems, databases, and compilers. Master binary trees, the four traversal algorithms, and the recursive thinking pattern that unlocks every tree interview problem.
The pattern that solves all contiguous subarray and substring problems in O(N). Learn fixed and variable window variants and recognise when to apply them.
The data structure that always gives you the minimum or maximum in O(1). Master heaps, heap operations, and the priority queue pattern that solves a whole class of interview problems.
The most important data structure in interviews. Understand how hash functions, collision resolution, and dynamic resizing work under the hood — and why HashMap is O(1) most of the time.
Make the locally optimal choice at each step and get a globally optimal solution. Learn when greedy works, when it doesn't, and the classic greedy patterns that appear in interviews.
The most versatile data structure in computer science. Understand how graphs model real-world problems, how to represent them in code, and the traversal algorithms that power social networks, maps, and compilers.
The hardest topic in DSA interviews, made systematic. Learn the two DP patterns — memoization and tabulation — and a step-by-step framework to solve any DP problem.
The data structure that gives you sorted data with O(log N) search, insert, and delete. Understand BST properties, operations, and why balance matters.
The two fundamental graph traversal algorithms. Understand when to use BFS vs DFS, how to implement both iteratively and recursively, and the interview problems each one solves.
The algorithmic technique for finding all solutions by exploring every possibility and abandoning paths that can't lead to a valid solution. Master the template that solves permutations, combinations, N-Queens, and Sudoku.
Strings are in almost every coding interview. Master the core techniques — sliding window, two pointers, hashing — and you'll handle any string problem.
Every developer should understand sorting algorithms — not just to use them, but to understand the trade-offs that apply to all algorithm design.
Binary search is more than just searching a sorted array. It's a thinking pattern that applies to a huge range of problems.
Queues power BFS, task scheduling, and rate limiting. Learn the three types of queues and when to use each.
Stacks are everywhere — your browser's back button, function call management, undo/redo. Learn how they work and how to use them to solve problems.
Linked lists are the gateway to understanding pointers, dynamic memory, and how more complex data structures like stacks and queues are built.
Recursion is one of the hardest concepts to grasp but once it clicks, it unlocks trees, graphs, dynamic programming and more.
Arrays are the most fundamental data structure. Master them and you'll solve 40% of coding interview problems.
Master Big O notation for your next DSA interview. Learn how to calculate time and space complexity with clear examples of O(1), O(n), O(n²), and O(log n).