30 LeetCode Interview Questions for 2026

Focus on the 30 LeetCode questions most likely to show up in interviews, organized by pattern, difficulty, and fresher vs. experienced level.

Common LeetCode questions: 30 most asked interview questions (2026)

LeetCode has over 2,500 problems. Most coding interviews test fewer than 50 of them — and those 50 draw from the same small set of patterns. If you're trying to figure out which LeetCode questions to actually focus on, this is the list. Thirty problems, organized by pattern and labeled by experience level (fresher or experienced), with a note on what each one actually tests. Start here.

Why the same LeetCode questions keep appearing in interviews

A widely cited heuristic in interview prep communities: roughly 10–12 core patterns account for the vast majority of coding interview questions. Companies like Google, Meta, Amazon, and ByteDance aren't inventing novel problems for every candidate. They're pulling from a shared pattern pool because what they're evaluating — your ability to recognize a problem shape, choose the right approach, and communicate your reasoning — doesn't require novelty. It requires consistency.

This article splits questions into two tiers. Fresher (0–2 years of experience): you're expected to solve the problem correctly, write clean code, and explain your approach. Experienced (3+ years): you're expected to recognize the pattern within two to three minutes, optimize for time and space, handle edge cases without prompting, and discuss trade-offs. Same problems, different bar.

The 12 core patterns behind every LeetCode interview question

Before the question list, here are the patterns that generate them. Recognizing which pattern applies is the first skill interviewers observe — before you write a line of code.

• Two Pointers — tests your ability to reduce O(n²) brute force to O(n) by scanning from both ends or with a fast/slow approach
• Sliding Window — tests efficient subarray/substring processing without recomputation
• Binary Search — tests divide-and-conquer thinking on sorted or monotonic data
• Depth-First Search (DFS) — tests recursive traversal of trees, graphs, and implicit state spaces
• Breadth-First Search (BFS) — tests level-order exploration and shortest-path reasoning
• Backtracking — tests systematic enumeration of combinations, permutations, and subsets
• Dynamic Programming — tests your ability to decompose problems into overlapping subproblems and cache results
• Greedy Algorithms — tests local-optimal decision-making and proof intuition
• Hashing / Hash Map — tests O(1) lookup design for frequency counting, deduplication, and complement searches
• Merge Intervals — tests sorting-plus-sweep logic for overlapping range problems
• Monotonic Stack — tests next-greater/next-smaller element reasoning in linear time
• Prefix Sum — tests precomputation for efficient range-sum queries

30 most common LeetCode interview questions

Questions are grouped by pattern category. Each entry includes the difficulty label (Easy / Medium / Hard), the experience tier (Fresher / Experienced), and one sentence on what the interviewer is actually evaluating.

Arrays & strings (6 questions)

Two Sum (Easy / Fresher) — The classic hash map warm-up. Tests whether you reach for O(n) lookup instead of nested loops.

Best Time to Buy and Sell Stock (Easy / Fresher) — Tests single-pass greedy thinking: track the minimum so far, update the maximum profit as you go.

3Sum (Medium / Fresher–Experienced) — Tests two-pointer technique on a sorted array and your ability to handle duplicate skipping cleanly.

Longest Substring Without Repeating Characters (Medium / Fresher) — The canonical sliding window problem. Tests whether you can maintain a window invariant while expanding and contracting.

Product of Array Except Self (Medium / Experienced) — Tests prefix/suffix array construction without division. Interviewers watch for whether you can do it in O(n) time and O(1) extra space.

Trapping Rain Water (Hard / Experienced) — Tests two-pointer mastery under a harder constraint. Often used as a signal that you can handle follow-ups on array problems without starting over.

Linked lists (4 questions)

Reverse Linked List (Easy / Fresher) — Fundamental pointer manipulation. If you can't do this in your sleep, nothing downstream works.

Merge Two Sorted Lists (Easy / Fresher) — Tests clean iterative or recursive merge logic. Interviewers look at how you handle the base cases.

Linked List Cycle (Easy / Fresher) — The fast/slow pointer introduction. Tests whether you know Floyd's algorithm and can explain why it works.

LRU Cache (Medium / Experienced) — Combines a hash map with a doubly linked list. Tests data structure design, not just algorithm knowledge. A favorite at companies that care about systems thinking.

Trees & graphs (7 questions)

Maximum Depth of Binary Tree (Easy / Fresher) — Entry-level DFS recursion. Tests whether you can write a clean recursive solution and state the base case.

Validate Binary Search Tree (Medium / Fresher–Experienced) — Tests DFS with constraint propagation. The common mistake — comparing only parent and child — is exactly what interviewers are screening for.

Binary Tree Level Order Traversal (Medium / Fresher) — The canonical BFS-on-a-tree problem. Tests queue usage and level-boundary handling.

Lowest Common Ancestor of a BST (Medium / Experienced) — Tests your ability to exploit BST properties rather than brute-forcing a general tree solution.

Number of Islands (Medium / Experienced) — BFS or DFS on a 2D grid. Tests graph traversal on implicit graphs, which requires a different mental model than traversing an adjacency list.

Course Schedule (Medium / Experienced) — Topological sort and cycle detection. Tests whether you can model a dependency problem as a directed graph and process it correctly.

Word Ladder (Hard / Experienced) — BFS for shortest transformation sequence. Tests your ability to define the state space and manage a visited set efficiently.

Dynamic programming (7 questions)

Climbing Stairs (Easy / Fresher) — The gentlest DP introduction. Tests whether you recognize the Fibonacci recurrence and can explain memoization vs. tabulation.

House Robber (Medium / Fresher) — 1D DP with a skip constraint. Tests state definition: "what's the best I can do ending at index i?"

Coin Change (Medium / Fresher–Experienced) — Unbounded knapsack variant. Tests bottom-up DP construction and whether you can explain why greedy fails here.

Longest Common Subsequence (Medium / Experienced) — 2D DP. Tests your ability to define a two-dimensional state and fill the table correctly.

Jump Game (Medium / Experienced) — Can be solved with greedy or DP. Tests whether you can argue for the greedy approach and prove it works.

Word Break (Medium / Experienced) — DP with string matching. Tests substring enumeration and memoization under a non-obvious state definition.

Edit Distance (Hard / Experienced) — The classic 2D DP problem. Tests whether you can handle insert/delete/replace transitions cleanly and explain the recurrence.

Heaps, greedy & backtracking (6 questions)

Top K Frequent Elements (Medium / Fresher–Experienced) — Tests heap usage or bucket sort. Interviewers often follow up with "can you do better than O(n log n)?"

Kth Largest Element in an Array (Medium / Experienced) — Tests min-heap of size k or quickselect. The follow-up is always about average vs. worst-case complexity.

Meeting Rooms II (Medium / Experienced) — Greedy with interval sorting. Tests whether you can model overlapping intervals as a sweep-line problem.

Subsets (Medium / Fresher) — The introductory backtracking problem. Tests recursive enumeration and your ability to explain the decision tree.

Combination Sum (Medium / Experienced) — Backtracking with pruning. Tests whether you can avoid redundant branches and explain your pruning logic.

Daily Temperatures (Medium / Experienced) — Monotonic stack. Tests whether you recognize the "next greater element" pattern and can implement it in one pass.

Fresher vs. experienced: what actually changes

The problems overlap. The expectations don't.

If you're a fresher, interviewers want to see correct output, reasonable complexity awareness, and — this is the part most people underestimate — clear communication while you solve. Can you talk through your approach before coding? Can you explain why you chose a hash map over a sorted array? The bar is "demonstrates structured thinking," not "produces the optimal solution in three minutes."

If you're experienced, the bar shifts. You're expected to identify the pattern quickly, jump to the optimal approach without exploring brute force first, handle edge cases without being prompted, and discuss trade-offs: time vs. space, readability vs. performance, average vs. worst case. At the 3+ year level, interviewers are evaluating engineering judgment, not just problem-solving speed.

One thing that's changed in 2026: interviewers know candidates use AI tools to practice. What they're testing now is whether you can explain your reasoning live — not just produce code. Candidates who practice only by submitting solutions and never by talking through their approach out loud are the ones who freeze when asked "why did you choose that data structure?"

Verve AI's Mock Interview lets you practice exactly that layer — explaining your approach out loud against a timed simulation, then getting structured feedback on your communication, not just your code.

How to actually use this list

Don't grind all 30 at once. Work by pattern, one category per session.

For each problem: solve it, then explain it back as if you're in an interview. Out loud. This is the step most people skip, and it's the step that matters most on the day.

Suggested sequencing for freshers: Arrays & Strings → Linked Lists → Trees & Graphs → Dynamic Programming → Heaps & Backtracking. Start with the patterns that have the most Easy-level problems so you build momentum before hitting DP.

Suggested sequencing for experienced engineers: Start with your weakest pattern category, not the easiest problems. If you already know two pointers cold but DP makes you sweat, open with Coin Change and Edit Distance. Your prep time is limited — spend it where the gap is.

A common approach in the prep community is a 30-day sprint: one pattern category per week, with the final week reserved for mixed-pattern review. That cadence works well with this list because the 30 problems are already grouped by pattern.

If you want to pressure-test your explanations before a real interview, Verve AI's Interview Copilot can run a timed mock on any of these problems and give you feedback on how you communicated your reasoning — not just whether your code passed.

The map, not the territory

Thirty questions. Twelve patterns. Two experience levels.

The goal isn't to memorize solutions. It's to recognize patterns fast and communicate clearly when it counts. Every problem on this list exists because it tests a pattern that shows up repeatedly in real interviews at real companies. Solve them with intention, explain them out loud, and you'll walk into your next coding interview having covered the ground that actually matters.

If you want to practice the communication layer — the part that separates "I know the answer" from "I got the offer" — try Verve AI's mock interview for free and see how your explanations hold up under pressure.