Blog
DSA pattern guides, head-to-head comparisons, and interview tips to help you crack coding interviews.
The Blind 75 LeetCode Problems: Complete Guide with Patterns
All 75 problems organized by DSA pattern instead of topic. Learn the optimal study order, which pattern each problem uses, and how to complete the list efficiently.
How to Solve Any LeetCode Problem: A 5-Step Framework
Stop staring at problems. Follow this 5-step framework: Understand, Identify the Pattern, Pseudocode, Implement, Optimize. Includes a pattern identification cheat sheet.
How to Prepare for FAANG Interviews in 3 Months: A Week-by-Week Plan
A detailed 12-week study plan covering which patterns to learn each week, daily schedule, how many problems to solve, and common mistakes that derail prep.
Dynamic Programming for Beginners: The Complete Introduction
DP demystified. Learn what overlapping subproblems and optimal substructure mean, top-down vs bottom-up approaches, and the 6 DP sub-patterns with step-by-step examples.
Two Pointers Technique Explained: From Basics to Advanced
Master the 4 types of two pointer problems: opposite-end, same-direction, two arrays, and partition. Full walkthroughs of Two Sum II, 3Sum, and Container With Most Water.
Greedy Algorithm Patterns: When Greedy Works (and When It Doesn't)
Learn the 5 classic greedy patterns, when greedy fails vs DP, and step-by-step solutions for Jump Game, Non-overlapping Intervals, and Task Scheduler.
Tree Traversal Patterns: BFS, DFS, Inorder, and Beyond
The 4 core traversals explained with recursive and iterative Python code. When to use which traversal, BFS vs DFS trade-offs, and 10 practice problems.
Hash Map Patterns for Coding Interviews: The Essential Guide
5 hash map patterns every engineer should know: frequency counting, two sum complement, grouping, caching, and sliding window combinations. With Python examples.
How to Recognize DP Problems in 10 Seconds
Learn the 3 signals that indicate dynamic programming: optimal substructure, overlapping subproblems, and counting/optimization phrasing. Plus keywords and a quick intro to each DP sub-pattern.
Top 50 LeetCode Problems Organized by Pattern
A curated list of 50 essential LeetCode problems grouped by the 7 pattern categories. Each problem includes number, difficulty, and which pattern to use.
How to Explain Your Approach to an Interviewer
The 4-step framework: Understand, Plan, Implement, Review. What interviewers look for and communication templates that work in any coding interview.
8 Common Mistakes in Coding Interviews (And How to Avoid Them)
Jumping to code too fast, not asking clarifying questions, wrong pattern, off-by-one errors, and more. Learn how to avoid these interview killers.
Pattern Combinations: When You Need Two Patterns
Some problems require multiple patterns: Binary Search + Greedy, BFS + DFS, Hash Map + Sliding Window. Learn when and how to combine patterns.
Top 10 LeetCode Patterns Every FAANG Candidate Must Know
Master these 10 essential patterns and you'll be able to solve 80% of coding interview problems. We break down each pattern with examples, complexity, and when to use it.
Two Pointers vs Sliding Window: When to Use Each
These two patterns look similar but solve very different problems. Learn the key differences, decision framework, and see side-by-side code examples.
How to Identify Sliding Window Problems: 5 Key Signals
Sliding window is one of the most common interview patterns. Learn the 5 signals that indicate a sliding window approach, common pitfalls, and a step-by-step solving framework.
BFS vs DFS: When to Use Which
Breadth-first search and depth-first search are foundational graph algorithms. Learn when each one shines, their space trade-offs, and how to pick the right one for any problem.
Dynamic Programming Patterns Explained: A Visual Guide
DP doesn't have to be scary. We break down 6 core DP patterns — Fibonacci, 0/1 Knapsack, Unbounded Knapsack, LCS, DP on Trees, and Grid DP — with recurrences and examples.
Time Complexity Cheat Sheet: From O(1) to O(n!)
A visual guide to common time complexities with examples, how to analyze nested loops, recursive calls, divide and conquer, and quick rules of thumb.
The Complete Guide to Sliding Window Problems
Fixed vs variable window, step-by-step template, and 5 example problems with approach sketches. Master one of the most powerful O(n) patterns.
Graph Patterns for Coding Interviews: BFS, DFS, Topological Sort, and Union-Find
When to use each pattern, code templates, and common problems. BFS for shortest path, DFS for components, topological sort for dependencies, union-find for connectivity.
Backtracking vs Dynamic Programming: How to Choose
A decision framework for choosing between backtracking and DP, side-by-side examples, and when each is more efficient.
Binary Search Beyond the Basics: 5 Advanced Variations
Standard, first occurrence, last occurrence, rotated array, and search on answer. Template for each variant with examples.
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