Top Backtracking LeetCode Questions Asked in Google Interviews (2026)

Backtracking is one of Google's most tested algorithmic topics in coding interviews — especially for L4 and L5 roles. If you're preparing for a Google SWE interview in 2026, mastering backtracking is non-negotiable.

This guide covers the most frequently asked backtracking LeetCode questions at Google, organized by difficulty and pattern type, so you can practice strategically and maximize your chances of cracking the coding round.

👉 Explore all Google LeetCode Interview Questions

👉 Practice all Backtracking problems on HackMNC

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Why Google Asks Backtracking Questions

Backtracking problems test your ability to:

• Explore a solution space systematically without brute-forcing every combination
• Prune invalid paths early — a key signal of algorithmic maturity that Google interviewers look for
• Write clean recursive code with clear base cases and state management
• Reason about time and space complexity of exponential-space trees

According to Google's LeetCode interview data, backtracking questions appear most frequently in L4+ onsite loops, often paired with an optimization follow-up (e.g., "Can you prune more aggressively?" or "Can you do this iteratively?").

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Most Asked Backtracking LeetCode Questions at Google (2026)

🟢 Easy

These warm-up problems are asked in phone screens and early coding rounds to verify that you understand recursive exploration.

• Letter Combinations of a Phone Number (LeetCode #17) — Classic DFS on a decision tree. Google loves asking follow-ups about iterative BFS approaches.
• Generate Parentheses (LeetCode #22) — Tests your ability to enforce constraints during recursion rather than filtering results after.

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🟡 Medium

Medium backtracking problems dominate Google's L3–L5 onsite rounds (52% of all Google LeetCode questions are medium difficulty). These are your highest-ROI problems to master.

• Subsets (LeetCode #78) — Foundation of the subset pattern. Clean up your recursive template here.
• Subsets II (LeetCode #90) — Introduces duplicate-handling logic; expect a Google interviewer to ask you to generalize.
• Combination Sum (LeetCode #39) — Reuse of elements makes this a fan-favorite at Google. Practice the pruning step carefully.
• Combination Sum II (LeetCode #40) — Same as above with a no-duplicate constraint. Often asked as a follow-up to #39.
• Permutations (LeetCode #46) — Core permutation template. Know how to swap in-place vs. use a visited array.
• Permutations II (LeetCode #47) — Duplicate-safe permutations. Tests sorting + backtracking together.
• Palindrome Partitioning (LeetCode #131) — DP + backtracking hybrid. Google frequently asks this for string-heavy roles.
• Word Search (LeetCode #79) — 2D grid backtracking. Know how to mark/unmark cells in-place without extra memory.

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🔴 Hard

Hard backtracking problems appear in later onsite rounds for senior roles (L5+). Google doesn't always expect a perfect solution; they want to see how you break down the problem.

• N-Queens (LeetCode #51) — The textbook backtracking problem. Know how to check diagonals efficiently with bitmasks.
• N-Queens II (LeetCode #52) — Count-only variant. Bitmask optimization is expected at senior levels.
• Sudoku Solver (LeetCode #37) — Deep constraint propagation. A Google interviewer may ask you to reason about worst-case backtracking depth.
• Word Search II (LeetCode #212) — Trie + backtracking. This is a hard problem that tests two topics at once — very Google-style.
• Expression Add Operators (LeetCode #282) — String parsing + backtracking + careful handling of multiplication precedence.

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How to Approach Backtracking in a Google Interview

1. State the recursive structure first — before writing code, explain: "At each step, I choose X, recurse, then undo that choice."
2. Name your base case explicitly — Google interviewers reward candidates who communicate their stopping condition before implementation.
3. Identify the pruning opportunity — almost every backtracking problem has a condition you can check early to cut branches. Mentioning this proactively signals L5-level thinking.
4. Analyze TC/SC — be ready to say "O(2^n * n) time for subsets" and explain why.
5. Handle duplicates intentionally — sort + skip is the most common pattern; don't let duplicates trip you up.

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Backtracking vs. Dynamic Programming at Google

A common interview trap: Google sometimes presents a problem that looks like backtracking but has an optimal DP solution (e.g., Word Break). If you see overlapping subproblems, mention the DP optimization even if you code the backtracking solution first. This "I see a memoization opportunity here" comment alone can move you from a hire to a strong hire.

For the DP versions, see: Top Dynamic Programming LeetCode Questions Asked in Google Interviews

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• Top Array LeetCode Questions Asked in Google Interviews
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