Topic Guide
Data Structures & Algorithms
Everything you need to master data structures and algorithms for coding interviews. From arrays and trees to dynamic programming and graph traversals.
19 guides in this collection
Interval Problems: Complete Interview Guide
Master interval problems for coding interviews. Learn to merge overlapping intervals, find gaps, and solve meeting rooms problems.
Greedy Algorithms: Complete Interview Guide
Master greedy algorithms for coding interviews. Learn when greedy works, common patterns like jump game and task scheduler.
Heap & Priority Queue: Complete Interview Guide
Master heaps for coding interviews. Learn min/max heaps, top K problems, merge K sorted lists, and find median from data stream.
Backtracking: Complete Interview Guide
Master backtracking for coding interviews. Learn the universal template for subsets, permutations, combinations, and constraint satisfaction.
Graph Algorithms: BFS and DFS Complete Guide
Master graph traversals for coding interviews. Learn BFS for shortest paths, DFS for cycle detection, topological sort, and classic problems.
Binary Tree Traversals: Complete Interview Guide
Master tree traversals for coding interviews. Learn preorder, inorder, postorder DFS and level-order BFS with recursive and iterative approaches.
Stack Pattern: Complete Interview Guide
Master stack patterns for coding interviews. Learn matching brackets, monotonic stack, expression evaluation, and common LeetCode problems.
Linked List Pattern Explained
Master linked list techniques for coding interviews. Learn singly vs doubly lists, cycle detection, in-place reversal, and the dummy head technique.
Binary Search: The Complete Interview Guide
Master binary search for coding interviews. Learn the template, common variations (lower/upper bound), and how to avoid off-by-one errors.
Dynamic Programming: A Practical Guide
Master dynamic programming with this step-by-step guide. Learn the patterns, recognize DP problems, and solve them systematically with real interview examples.
Big O Notation Explained
Complete guide to Big O notation, algorithmic complexity, and performance analysis. Learn to calculate time and space complexity from code with real examples.
Hash Maps: When and Why
Master hash maps (hash tables, dictionaries) for coding interviews. Learn collision resolution, load factor, and solve common problems like Two Sum and anagrams.
Two Pointers Pattern Explained
Master the two pointers technique for solving array and string problems efficiently. Learn when to use it and common problem patterns.
Sliding Window: When and How to Use It
Understand the sliding window pattern for solving subarray and substring problems. Includes fixed-size and dynamic window examples.
Matrix Traversal Patterns: DFS, BFS & Path Finding
Master matrix/grid traversal patterns including DFS, BFS, flood fill, islands, and shortest path algorithms for coding interviews.
Monotonic Stack and Queue: Interview Pattern Guide
Master monotonic stack and queue patterns for next greater element, sliding window maximum, and histogram problems.
Top K Elements Pattern: Heap Interview Guide
Master the Top K elements pattern using heaps for finding largest/smallest K elements, Kth largest, and frequency problems.
Trie Data Structure: Complete Interview Guide
Master the trie (prefix tree) for solving autocomplete, spell checking, and word search problems. Learn implementation, variations, and common interview patterns.
Union-Find (Disjoint Set Union): Complete Interview Guide
Master the Union-Find data structure for solving connected components, cycle detection, and dynamic connectivity problems in coding interviews.
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