Top 20 Google Coding Interview Questions (2026)

Google coding interviews usually mix classic data structures and algorithms with open-ended prompts that test how you think under pressure. Expect questions where the first step is clarifying assumptions, then choosing the right model, then explaining tradeoffs clearly. The 20 questions below are some of the Google coding prompts candidates mention most often, and they give a good sense of what to practice.

System design with coding fundamentals

1. Design a restaurant waitlist system
   
   This kind of prompt checks whether you can turn a messy real-world workflow into sensible data structures and operations. Interviewers want to hear how you handle party sizes, estimated wait times, cancellations, and table assignment rules without losing sight of time complexity.

2. Build a Next-Word Predictor
   
   This is a small product-style question that blends strings, counting, and API thinking. A good answer starts with a simple frequency-based model, then covers edge cases like punctuation, ties, unknown words, and memory use.

3. Design autocomplete with Trie
   
   Autocomplete is a standard Google topic because it connects tries, ranking, and query behavior at scale. The interviewer is usually checking whether you know why a trie helps with prefix lookup and how you would rank or cap suggestions efficiently.

String processing and dictionary lookup

1. Check if all substrings are anagrams of words
   
   This question is about spotting repeated work inside substring checks and reducing it with frequency counts or sliding windows. The main skill under test is whether you can avoid brute force and reason clearly about character signatures.

2. Check if all substrings are dictionary words
   
   Interviewers ask this to see whether you can combine substring generation with fast membership testing. A strong discussion usually compares hashing, tries, and pruning ideas, especially if the naive approach blows up fast.

3. Return dictionary words matching a prefix
   
   This is a simpler prefix search problem, but Google interviewers often care more about how you structure the search than about writing a lot of code. You should think about trie-based lookup, sorted arrays with binary search, and how output size affects complexity.

Scheduling and interval questions

1. Compute minimum number of rooms needed
   
   This is a classic interval overlap problem, and it comes up often because it shows whether you know the sweep-line pattern. The expected direction is usually sorting starts and ends, or using a min-heap to track active meetings.

2. Compute minimum rooms for time intervals
   
   This looks very close to the previous one, and that is part of the point. Google often repeats core patterns with different wording, so you should practice spotting the same interval-overlap structure quickly.

3. Compute servers needed for daily recurring jobs
   
   This extends interval reasoning into recurring schedules, where wraparound and repetition can break a solution that only works on a single timeline. The interviewer is checking whether you notice periodicity and model overlapping demand carefully.

4. Find safe travel intervals between planet influences
   
   This is another interval problem, but with a trickier presentation and usually more corner cases. A good approach starts by converting "unsafe" regions into merged intervals and then taking the complement over the valid travel range.

Graphs and traversal

1. Recommend top-K movies from similarity graph
   
   This question checks whether you can traverse a graph while keeping ranking logic under control. Expect to discuss BFS or best-first exploration, deduplication, and how to maintain the top K candidates without sorting everything.

2. Can you reach target with distance-threshold edges?
   
   This is the kind of graph prompt where the trick is building the graph model correctly before searching it. The interviewer is watching for whether you can translate a geometric or threshold rule into edges and then choose BFS, DFS, or Union-Find based on the exact ask.

3. Compute shortest delivery route with dangerous stops
   
   Shortest-path questions get more interesting once constraints are layered onto the path. You should be ready to explain whether dangerous stops can be filtered out first, encoded as state, or handled with a modified Dijkstra-style search.

4. Validate parent array forms a tree
   
   This is a graph-validation problem in disguise. Google likes questions like this because they test basic structural reasoning, like detecting one root, rejecting cycles, and confirming connectivity with minimal code.

Probability, dynamic programming, and game-style reasoning

1. Compute winning probability on 1D dice walk
   
   This is a harder screen question because it asks for both mathematical modeling and clean implementation. The usual path is to define states carefully, write a recurrence, and then decide whether memoization or bottom-up DP gives the clearest answer.

2. Determine if a 14-tile hand is winning
   
   This problem tests recursive search, counting, and pruning. The interviewer wants to see whether you can turn a rule-heavy game into a small state space and avoid repeated work with sorted representations or frequency maps.

Arrays, range updates, and offline thinking

1. Apply Range Overwrite Queries
   
   This onsite problem is harder than it first appears because simple per-query updates can be too slow. Interviewers ask it to see whether you know offline processing ideas, segment structures, or reverse-order tricks that skip already resolved positions.

2. Find largest group of two-digit numbers sharing digits
   
   This is an easy question on paper, but it still checks whether you can spot the right representation quickly. Usually the clean move is to model shared digits as connectivity or grouping through a compact signature.

Small DP and greedy-style take-home questions

1. Maximize coins with tokens moving by +3
   
   This kind of take-home problem tests whether you can find a recurrence in a very small rule set. Even for easier prompts, Google is often looking for a short, clear explanation of state transitions and boundary cases.

2. Compute max coins with 3-step token moves
   
   This is closely related to the previous prompt and is good practice for recognizing pattern reuse. If two questions share the same skeleton, that is a reminder to study ideas, not memorized answers.

What these questions say about Google interview prep

A few patterns stand out. Google asks a lot of questions where the wording is specific, but the core idea is standard: intervals, tries, graph traversal, dynamic programming, or state modeling. That means your prep should focus on two things, spotting the pattern quickly and talking through tradeoffs without rambling.

It also helps to practice clarifying questions before coding. In autocomplete and waitlist design, assumptions matter a lot. In interval and graph questions, details like inclusivity, duplicate entries, disconnected nodes, and wraparound time ranges can change the solution.

Several of these prompts are medium difficulty but get hard if you jump into implementation too early. Write down the data model, identify the expensive step, and ask yourself what has to be fast. That habit often makes the right approach much easier to find.

If you want more practice beyond this list, PracHub has 153+ Google coding questions, including these popular ones and many more reported by candidates.