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LeetCodeFAANGPatternsInterview Prep

The 50 Best LeetCode Problems for Coding Interviews [2026]

· 11 min read

Syed Peera Saheb

Software Engineer · 5+ years in tech interviews

Summary

50 problems hand-picked across 10 patterns — each appeared in real FAANG interviews and gives the best return on prep time.

How these 50 were chosen

These problems were selected using three criteria: (1) Frequency — reported in real interview question databases from Google, Meta, Amazon, Apple, and Microsoft in 2023–2025. (2) Pattern coverage — each problem is the cleanest representative of its pattern. Solving it gives you a transferable template, not just the answer to one problem. (3) Difficulty calibration — roughly 60% Medium, 30% Hard, 10% Easy warmups. If you solve all 50 correctly with no hints, you are interview-ready for any tier-1 tech company.

Arrays and hashing (problems 1–8)

1. Two Sum (LC 1) — the hash map lookup template. 2. Group Anagrams (LC 49) — sorted string as hash key. 3. Top K Frequent Elements (LC 347) — bucket sort trick beats heap. 4. Product of Array Except Self (LC 238) — prefix/suffix pass, no division. 5. Longest Consecutive Sequence (LC 128) — hash set, O(n). 6. Valid Sudoku (LC 36) — multi-constraint hash tracking. 7. Encode and Decode Strings (LC 271) — delimiter-free serialization. 8. Subarray Sum Equals K (LC 560) — prefix sum + hash map, count of subarrays.

Two pointers and sliding window (problems 9–16)

9. Container With Most Water (LC 11) — converging pointers, greedy step. 10. Trapping Rain Water (LC 42) — two pointers tracking max left/right. 11. 3Sum (LC 15) — sort + two pointers, skip duplicates pattern. 12. Minimum Window Substring (LC 76) — sliding window with character counts. 13. Longest Substring Without Repeating Characters (LC 3) — variable window + set. 14. Permutation in String (LC 567) — fixed window, frequency match. 15. Sliding Window Maximum (LC 239) — monotonic deque. 16. Longest Repeating Character Replacement (LC 424) — window with most-frequent count trick.

Binary search (problems 17–20)

17. Find Minimum in Rotated Sorted Array (LC 153) — binary search on rotated array invariant. 18. Search in Rotated Sorted Array (LC 33) — which half is sorted? 19. Koko Eating Bananas (LC 875) — binary search on answer, classic template. 20. Median of Two Sorted Arrays (LC 4) — binary search on partition, Hard, frequently asked at Google.

Trees and graphs (problems 21–34)

21. Invert Binary Tree (LC 226) — recursive swap, tree DFS warmup. 22. Maximum Depth of Binary Tree (LC 104) — DFS, base case matters. 23. Binary Tree Maximum Path Sum (LC 124) — postorder, global max trick. 24. Lowest Common Ancestor of a Binary Tree (LC 236) — recursive LCA pattern. 25. Serialize and Deserialize Binary Tree (LC 297) — BFS/preorder round-trip. 26. Construct Binary Tree from Preorder and Inorder (LC 105). 27. Number of Islands (LC 200) — DFS flood fill on grid. 28. Clone Graph (LC 133) — DFS + hash map for visited nodes. 29. Course Schedule (LC 207) — cycle detection, topological sort. 30. Word Ladder (LC 127) — BFS on word graph, very common at Google. 31. Pacific Atlantic Water Flow (LC 417) — multi-source BFS/DFS. 32. Rotting Oranges (LC 994) — multi-source BFS. 33. Alien Dictionary (LC 269) — topological sort from character ordering. 34. Network Delay Time (LC 743) — Dijkstra, weighted shortest path.

Dynamic programming (problems 35–44)

35. Climbing Stairs (LC 70) — Fibonacci DP, the entry point. 36. House Robber (LC 198) — skip/take recurrence. 37. Coin Change (LC 322) — unbounded knapsack template. 38. Longest Increasing Subsequence (LC 300) — 1D DP or patience sort. 39. Longest Common Subsequence (LC 1143) — 2D DP, string/sequence problems. 40. Edit Distance (LC 72) — 2D DP, very common at Google. 41. Partition Equal Subset Sum (LC 416) — 0/1 knapsack to boolean. 42. Word Break (LC 139) — string segmentation DP. 43. Best Time to Buy and Sell Stock III (LC 123) — state machine DP, at most 2 transactions. 44. Burst Balloons (LC 312) — interval DP, Hard, memorable pattern.

Heap, backtracking, and other patterns (problems 45–50)

45. Merge K Sorted Lists (LC 23) — min-heap merge, O(n log k). 46. Find Median from Data Stream (LC 295) — two heaps. 47. Combination Sum (LC 39) — backtracking template, reusable elements. 48. N-Queens (LC 51) — backtracking with pruning on diagonals. 49. LRU Cache (LC 146) — doubly linked list + hash map design. 50. Design Add and Search Words Data Structure (LC 211) — Trie with wildcard DFS. These final 6 span heap (45–46), backtracking (47–48), design (49), and Trie (50) — the four patterns most likely to appear as a second problem in a two-problem interview round.

Frequently Asked Questions

What are the 10 most important LeetCode problems to solve?
If you could only do 10: Two Sum (hash map), Longest Substring Without Repeating Characters (sliding window), Binary Tree Maximum Path Sum (tree DFS), Number of Islands (graph BFS/DFS), Course Schedule (topological sort), Coin Change (DP), Merge K Sorted Lists (heap), Word Ladder (BFS), LRU Cache (design), and Find Median from Data Stream (two heaps). These 10 cover 9 of the most critical patterns.
How long does it take to solve 50 LeetCode problems with understanding?
At a pace of 2 problems per day with genuine understanding (45-60 min each, reviewing the optimal solution, writing notes on the pattern): approximately 4-5 weeks. Rushing to solve 50 in 2 weeks by looking up hints quickly results in surface-level memorization rather than pattern recognition — the skill that actually transfers to unseen interview problems.
Are LeetCode Hard problems required for FAANG interviews?
Yes — you should solve at least 20-30 hard problems before interviewing at Google, Meta, or Amazon. These companies frequently ask medium-hard and hard problems, especially in later rounds. However, you do not need to solve all 700+ hard problems — focus on the hard problems that are most frequently reported in interview databases and that test canonical hard patterns (interval DP, advanced graph algorithms, complex sliding window).
Which company asks the hardest LeetCode problems?
Google and Stripe consistently ask the hardest problems, followed by Citadel (finance) and Jane Street (quantitative). Google emphasizes graphs and DP with hard variants. Meta tends toward medium problems with high volume (2 problems per round). Amazon varies by team but often has medium DP and tree problems. Microsoft is generally medium difficulty. Apple has a reputation for asking more algorithm theory questions.

Syed Peera Saheb

Software Engineer · 5+ years · ServiceNow

Software engineer with hands-on experience passing technical interviews at top tech companies. Built Coding Prep Guide to share the pattern-first prep strategy that actually works. Writes about DSA, system design, and interview strategy.

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