30 Adobe LeetCode Interview Questions for 2026

Prepare for Adobe coding rounds with 30 LeetCode interview questions, key topic areas, process insights, and a focused 2026 prep strategy.

Adobe LeetCode Interview Questions: 30 Most Asked (2026)

Adobe LeetCode interview questions follow patterns. If you know which ones recur, you can cut weeks off your prep and focus on what Adobe interviewers actually evaluate — not just whether you get the right answer, but how you communicate your approach, handle edge cases, and respond to follow-ups. This guide covers the 30 most commonly reported problems organized by difficulty, a breakdown of Adobe's interview process, and a prep workflow that mirrors the real thing.

How Adobe's interview process works

Adobe's loop is structured and, by most accounts, calmer than the average big-tech gauntlet. Here's what to expect:

• Recruiter / HR screen — Experience overview, notice period, expected compensation. This is a filter, not a technical round. Community reports suggest roughly 70% of candidates pass this stage.
• Hiring manager round — Project deep dive and scenario-based technical questions. Communication is assessed explicitly here. Expect to walk through a past project in detail and answer "what would you do if..." prompts.
• DSA / coding round(s) — LeetCode-style problems, typically easy-to-medium. Interviewers are frequently described as calm and experienced. Hints are sometimes given — take them. Multiple candidates report interviewers who guide rather than grill.
• Take-home or timed test — Not universal. Appears for some roles and locations. Treat it like a real coding round: clean code, comments, edge cases handled.
• On-site / final rounds — Up to five rounds total. Stamina matters. Pace yourself.

Role variation is real. Pure SWE loops lean heavily on DSA and system design. AI/ML roles mix domain knowledge — computer vision, model evaluation, scenario-based ML questions — with easier DSA. Location matters too: Noida roles may weight C/C++ fundamentals more heavily than US-based positions.

What Adobe actually tests in LeetCode rounds

The topic distribution across confirmed candidate reports clusters around these areas:

• Arrays and sliding window — The bread and butter. Expect subarray sums, two-pointer problems, and window-based optimization.
• Strings and parsing — Including edge cases like overflow handling in string-to-integer conversion (atoi). Adobe interviewers care about how you handle boundary conditions.
• Dynamic programming — The House Robber pattern shows up repeatedly. Classic 1D and 2D DP problems are fair game.
• Stacks and monotonic structures — Container With Most Water is a confirmed question. Interviewers may have a preferred solution pattern (e.g., stack-based), so communicate your approach before coding and adjust if they steer you.
• Trees and graphs — BFS, DFS, tree traversal, and path-sum variants.
• Deque and cyclic indexing — Confirmed in candidate reports. Pattern recognition matters here — one candidate solved this type in 15-20 minutes because they'd seen the pattern before.
• Divide and conquer / merge-sort variants — Count of Smaller Numbers After Self is a confirmed hard-level question that tests merge-sort or BIT approaches.

One thing that comes through consistently: Adobe interviewers reward candidates who articulate their approach and ask clarifying questions before writing code. State your Big-O before and after optimizing. Don't just solve — explain.

Adobe LeetCode interview questions — the 30 most asked

The questions below are drawn from confirmed candidate reports and the topic patterns Adobe interviews consistently cover. Where a specific problem is confirmed by name in interview accounts, it's noted. The rest are canonical LeetCode problems that match Adobe's documented topic areas. These are organized as commonly tested patterns, not statistically ranked frequencies.

Easy / warm up (questions 1 10)

1. Two Sum — Array, hash map. The universal warm-up. Tests whether you reach for the O(n) solution immediately or start with brute force.

2. Best Time to Buy and Sell Stock — Array, single pass. Tracks a running minimum. Adobe's easy rounds often start here or with a close variant.

3. Valid Parentheses — Stack. Clean stack usage and edge-case handling (empty string, unmatched brackets).

4. Merge Two Sorted Lists — Linked list, two-pointer. Tests pointer manipulation and clean termination logic.

5. Maximum Subarray (Kadane's Algorithm) — Array, DP. A one-liner in concept, but interviewers want to hear you explain the state transition.

6. Reverse Linked List — Linked list. Iterative vs. recursive — know both and explain the trade-off.

7. String to Integer (atoi) — String parsing, overflow handling. Confirmed in Adobe interview reports. The edge cases are the entire point: whitespace, signs, overflow to INT_MAX/INT_MIN, non-numeric characters.

8. House Robber — 1D DP. Confirmed in Adobe interview reports. Classic "can't pick adjacent elements" pattern. Explain the recurrence relation clearly.

9. Climbing Stairs — DP / Fibonacci. Simple but tests whether you recognize the DP structure and can optimize space.

10. Intersection of Two Linked Lists — Linked list, two-pointer. Tests pointer arithmetic and the "equalize lengths" trick.

Medium / core round (questions 11 22)

11. Container With Most Water — Two-pointer. Confirmed in Adobe interview reports. At least one interviewer was described as preferring a stack-based approach. Know both and lead with whichever you're more comfortable explaining.

12. 3Sum — Array, sorting, two-pointer. Duplicate handling is where most candidates slip. Walk through your dedup logic explicitly.

13. Longest Substring Without Repeating Characters — Sliding window, hash set. Adobe's string questions often test this pattern.

14. Group Anagrams — Hash map, string sorting. Tests your choice of key representation and Big-O awareness.

15. Product of Array Except Self — Array, prefix/suffix. The "no division" constraint is the real question.

16. Binary Tree Level Order Traversal — BFS, queue. Clean BFS implementation with level tracking.

17. Number of Islands — Graph, BFS/DFS. Grid traversal with visited tracking. Explain your choice of BFS vs. DFS and why.

18. Course Schedule — Graph, topological sort. Tests cycle detection in a directed graph. Know both Kahn's algorithm and DFS-based approaches.

19. Decode Ways — 1D DP, string. Tricky edge cases with '0'. Walk through examples before coding.

20. Rotate Image — Matrix, in-place. Transpose + reverse. Interviewers want to see you handle the in-place constraint cleanly.

21. Sliding Window Maximum — Deque. Matches the deque/cyclic indexing pattern confirmed in Adobe reports. Monotonic deque is the optimal approach — explain why a naive solution is too slow.

22. LRU Cache — Hash map + doubly linked list. Design-flavored coding problem. Tests data structure composition and clean API design.

Hard / senior / experienced track (questions 23 30)

23. Count of Smaller Numbers After Self — Merge sort or BIT. Confirmed in Adobe interview reports. Tests whether you can adapt merge sort to count inversions. Senior candidates should expect this tier.

24. Trapping Rain Water — Two-pointer or stack. A classic that tests multiple valid approaches. Explain trade-offs between them.

25. Median of Two Sorted Arrays — Binary search. O(log(min(m,n))) is the target. The binary search partitioning logic is the hard part — practice explaining it out loud.

26. Merge K Sorted Lists — Heap / divide and conquer. Tests your ability to choose between a min-heap approach and recursive merging, and to articulate the Big-O difference.

27. Word Ladder — BFS, graph. The key insight is treating each word as a node. Explain your adjacency construction.

28. Longest Increasing Subsequence — DP or binary search with patience sorting. Know the O(n log n) approach and why it works.

29. Minimum Window Substring — Sliding window, hash map. The hardest sliding window variant. Edge cases with duplicate characters in the target string.

30. Serialize and Deserialize Binary Tree — Tree, BFS/DFS, string design. Tests end-to-end thinking: encoding, decoding, and handling null nodes.

Hard problems appear more often for senior roles and in second or third coding rounds. If you're interviewing at the 3+ years experience level, expect at least one problem from this tier.

Fresher vs. experienced — what changes

Freshers and new grads should expect easy-to-medium DSA, language fundamentals (C++, Java, or Python basics), and straightforward data structure questions. Interviewers may provide hints and guide you toward the solution. Project discussion is lighter — focus on academic or personal projects you can explain clearly.

Experienced candidates (3+ years) face medium-to-hard DSA, deeper project dives where you'll need to defend design decisions, and scenario-based questions that test judgment under ambiguity. AI/ML roles add domain-specific questions — computer vision, model evaluation, data pipeline design. Less hand-holding. More follow-ups.

Both tracks share one thing: Adobe interviewers consistently reward candidates who communicate their thinking. Articulate your approach before coding. Ask clarifying questions. State assumptions. This isn't optional — it's part of the evaluation.

How to practice Adobe LeetCode interview questions

Solo grinding isn't enough. Adobe's interview explicitly evaluates communication, not just correctness. If you practice silently in an IDE with autocomplete, you're training for a different test than the one you'll take.

A better approach:

• Set a 45-60 minute timer. Real rounds are timed. Practice under the same constraint.
• Restate the problem aloud before touching code. Put it in your own words.
• Ask clarifying questions. Even in solo practice, write down the assumptions you'd confirm with an interviewer.
• Build example inputs and expected outputs. Walk through at least two before coding.
• Brainstorm solutions and state Big-O before you implement. This is the step Adobe interviewers care about most.
• Implement without IDE hints. Use a plain text editor or whiteboard.
• Test your code manually. Trace through your examples by hand.
• Optimize and explain the trade-off. Can you improve time? Space? What's the cost?

The communication layer is what separates candidates who pass from candidates who solve the problem but still get rejected. Practice with a mock interviewer whenever possible — a friend, a study partner, or an AI tool that gives real-time feedback on your explanations and code walk-throughs.

Verve AI's Interview Copilot lets you run timed mock sessions that evaluate not just your solution but how you explain it — the pacing, the structure, the clarity of your reasoning. If you're drilling the communication habits Adobe rewards, that feedback loop matters more than solving ten extra problems in silence.

Quick prep checklist before your Adobe interview

• Review the confirmed topic areas: arrays, strings, DP, stacks, trees, graphs, deque/cyclic indexing.
• Practice medium problems timed at 30-45 minutes. Don't skip the explanation step.
• Prepare a 2-3 minute project walkthrough for the hiring manager round. Know your design decisions and trade-offs cold.
• Know your Big-O for every solution you practice — before and after optimizing.
• If applying for AI/ML: brush up on computer vision basics, model evaluation metrics, and scenario-based ML questions.
• Expect up to five rounds. Pace yourself mentally. Stamina is part of the test.
• Note the 6-month cool-off period if rejected. Plan your application timing accordingly.

Thirty problems, practiced well and explained clearly, will take you further than two hundred problems solved in silence. Adobe's loop rewards the candidate who communicates — not just the one who codes.