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DSA pattern guides, head-to-head comparisons, and interview tips to help you crack coding interviews.

dynamic-programmingpatternsrecognition

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.

8 min read
leetcodepatternsstudy-guide

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.

12 min read
interviewcommunicationframework

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.

9 min read
interviewmistakestips

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.

10 min read
patternscombinationsadvanced

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.

11 min read
patternsfaanginterview

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.

8 min read
two-pointerssliding-windowcomparison

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.

7 min read
sliding-windowtechniqueinterview

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.

7 min read
bfsdfsgraphstrees

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.

8 min read
dynamic-programmingpatternsguide

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.

10 min read
complexitycheatsheetinterview

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.

9 min read
sliding-windowguidetemplates

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.

10 min read
graphsbfsdfsinterview

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.

11 min read
backtrackingdynamic-programmingcomparison

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.

10 min read
binary-searchtemplatesadvanced

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.

9 min read

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