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Master every DSA pattern. Track your progress. Ace your coding interviews.
LeetCode patterns are reusable algorithmic techniques — such as Two Pointers, Sliding Window, Dynamic Programming, and Graph BFS/DFS — that apply to entire categories of coding problems. Instead of memorizing hundreds of individual solutions, mastering a pattern lets you recognize and solve any problem that follows that template. This pattern-based approach is the single most effective strategy for FAANG and SDE interview preparation at companies like Google, Amazon, Meta, Apple, and Microsoft.
This free tracker organizes all 88 major DSA patterns into 15 categories with 368 hand-curated LeetCode problems, letting you systematically work through each one and measure your readiness.
Most engineers preparing for coding interviews grind random LeetCode problems — spending hundreds of hours without a clear roadmap. Research and experience show that pattern-based DSA preparation is 3–5× more efficient. When you recognize that "this problem uses the Two Pointers pattern" instead of memorizing a specific solution, you unlock the ability to solve problems you've never seen before.
This free LeetCode patterns tracker gives you a structured preparation roadmap that mirrors how interviewers think. Every problem in FAANG interviews belongs to one of ~88 algorithmic patterns. Master the patterns, not the problems.
The Two Pointers technique uses two indices that move through a data structure — often converging from opposite ends or moving at different speeds. It reduces O(n²) brute-force solutions to O(n) linear time. Essential for sorted array problems, linked list cycle detection (fast & slow pointers), palindrome validation, and container maximization. Classic problems: Two Sum II, 3Sum, Container With Most Water, Linked List Cycle.
The Sliding Window pattern maintains a dynamic subset of elements as a window slides across an array or string. Fixed-size windows solve subarray sum/average problems in O(n). Variable-size windows handle constraint-based substring problems. Monotonic deque variants solve max/min in windows. Classic problems: Minimum Window Substring, Longest Substring Without Repeating Characters, Sliding Window Maximum.
Dynamic Programming is the most tested topic in FAANG interviews. It decomposes complex problems into overlapping subproblems using memoization or tabulation. This tracker covers all major DP subtypes: 1D Fibonacci-style (Climbing Stairs, House Robber), 1D Knapsack (Coin Change, Partition Equal Subset Sum), 2D LCS/Edit Distance, Grid DP, Interval DP, and LIS. Mastering all 11 DP patterns here is sufficient for any SDE interview.
Graph algorithms — BFS, DFS, Topological Sort, Dijkstra's, and Union-Find — appear in nearly every senior SDE interview. This tracker covers 8 distinct graph patterns including cycle detection, connected components, shortest paths (Dijkstra & Bellman-Ford), island counting, and disjoint set union. Classic problems: Number of Islands, Course Schedule, Word Ladder, Network Delay Time.
Binary Search extends far beyond sorted arrays. The "search on answer" technique applies binary search to monotonic functions and optimization problems — reducing O(n) or O(n²) solutions to O(log n). Classic problems: Koko Eating Bananas, Capacity to Ship Packages, Find Peak Element, Median of Two Sorted Arrays.
Backtracking systematically explores all possible solutions by building candidates incrementally and abandoning ("backtracking") paths that violate constraints. It powers permutation generation, subset enumeration, constraint satisfaction (N-Queens, Sudoku), and word search in grids. Understanding the include/exclude decision tree is the key to mastering this pattern.
Use this structured plan with the tracker to cover all 88 patterns in 8 weeks. Aim for 5–8 problems per day and always write your approach in the notes section before submitting.
Effective coding interview preparation follows a three-phase approach. In the first phase (weeks 1–3), build your foundational pattern knowledge: start with Two Pointers and Sliding Window — they appear in nearly every interview and share underlying mechanics that unlock faster learning of harder patterns.
In the second phase (weeks 4–6), tackle the high-frequency patterns that make or break FAANG interviews: Tree DFS/BFS, Graph traversal, and Dynamic Programming. Use this tracker to ensure you haven't skipped any pattern sub-type — interviewers know exactly which DP variant to test if they see you've practiced Coin Change but not Knapsack.
In the final phase (weeks 7–8), do timed mock problem sets, review your notes, and optimize your approach explanations. Your goal is to reach the point where you recognize a pattern within 30 seconds of reading a problem — that's when you're interview-ready.
Effective coding interview preparation follows a three-phase approach. In the first phase (weeks 1–3), build foundational pattern knowledge: start with Two Pointers and Sliding Window — they appear in almost every interview and share underlying mechanics that unlock faster learning of harder patterns.
In the second phase (weeks 4–6), tackle the patterns that make or break FAANG interviews: Tree DFS/BFS, Graph traversal, and Dynamic Programming. Use this tracker's per-category progress bars to ensure you haven't skipped any sub-type — interviewers know exactly which DP variant to test.
In the final phase (weeks 7–8), do timed mock problem sets, review your notes, and optimize your approach explanations. Your goal: recognize a pattern within 30 seconds of reading a problem. That's when you're interview-ready. Then use our Resume Checker to ensure your skills show up on paper.
LeetCode patterns are reusable algorithmic templates — like Two Pointers, Sliding Window, and Dynamic Programming — that apply to whole categories of problems. They matter because interviewers don't randomly pick problems; they pick problems from known patterns. Learning the pattern means you can solve any variant, not just the ones you've seen.
Most engineers need 8–16 weeks of consistent daily practice. If you solve 5–8 problems per day across all major patterns using a structured tracker, you can be interview-ready in 8 weeks. Don't rush — understanding the pattern deeply is more valuable than volume.
Follow a pattern-based study plan: start with Arrays and Two Pointers, move to Trees and Graphs, then tackle Dynamic Programming. Use a tracker (like this one) to ensure you've covered all patterns. Write approach notes for every problem you solve. Do 2–3 mock interviews in your final week. Aim for 150–300 problems total before your interview.
Yes — 100% free, forever. You can start tracking immediately without any account. Sign in with Google for free cloud sync (powered by Firebase) so your progress is preserved across all your devices. No credit card, no premium tier, no hidden costs.
Striver's SDE Sheet organizes problems by broad topic (Arrays, Linked Lists, etc.). LeetCode Pattern Tracker organizes by specific algorithmic pattern — e.g., "Fast & Slow Pointers," "Monotonic Stack," "Union-Find DSU" — which is more granular and better for interview readiness. It also includes cloud sync, per-problem notes, and a live progress dashboard.
Quality over quantity. Solving 150–300 problems across all major patterns — and being able to explain the time and space complexity of each — is sufficient for most FAANG-level interviews. If you can solve any problem in each pattern confidently, you're ready regardless of the total count.