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Google Online Assessment
Overview
Google online assessment (OA) is the first hard filter for most fresher, campus, and off-campus SDE-style drives. This page covers the Google OA format, what happens after you clear it, sample Google OA questions with approaches, an 8-week prep plan, and mistakes that sink otherwise-strong candidates.
Patterns below are from student reports for 2025-2026. Platforms and section names can change by drive. Always confirm the college placement email for your window.
Google hiring flow after the OA
| Stage | What candidates report | What you must show |
|---|---|---|
| 1. Online assessment | Often 1-2 timed coding problems (sometimes plus Google foobar-style invites for some paths) | Correctness + reasonable complexity under time |
| 2. Technical interviews | Phone / virtual onsite style rounds heavy on algorithms and problem solving | Explain approach, edge cases, complexity |
| 3. Later rounds | Multiple interviewers; Googleyness / behavioral; hiring committee review on many loops | Depth beyond the OA pattern |
| 4. HR / offer | Role, location, CTC discussion | Consistency with resume |
Google Online Assessment format
Test structure
| Component | From student reports details |
|---|---|
| Platform | HackerRank, CodeSignal, or Google-hosted OA depending on program |
| Duration | Often 45-90 minutes for coding OA variants |
| Question mix | 1-2 hardish coding problems; occasionally follow-ups inside the same prompt |
| Languages | C++, Java, Python, Go (confirm invite) |
| Scoring | Correctness + efficiency; partial credit rare on hard hidden tests |
| Advance rate | Highly selective; many candidates report OA as a steep first round |
What makes Google OA feel distinct
- Difficulty skews medium-hard to hard more often than service-company tests
- Clean code and complexity analysis are expected even in the OA write-up
- Follow-up constraints (“now do it in O(n)”) appear in interviews more than OA, but prepare anyway
- Domain flavor is general CS, not a long aptitude paper
Question types you should expect
Core DSA
- Graphs (shortest paths, topological order, Union-Find)
- Trees / recursion / divide and conquer
- Advanced hashing, strings, sliding window
- DP on sequences and grids
- Math-flavored combinatorics when constraints hint it
Secondary / role-dependent
- Careful I/O and edge cases on platform templates
- Occasional multi-part problems where part B depends on part A design
What usually does not appear in the OA
- Long verbal/quant aptitude like TCS NQT
- Full distributed-system design (later rounds)
- Product sense interviews for pure SWE OA paths
Sample Google Online Assessment questions
Question 1: shortest path in a weighted grid
Q: Move from top-left to bottom-right; each cell has a cost. Find minimum path cost (4-dir).
Dijkstra on the grid (or 0-1 BFS if costs are 0/1). Avoid plain BFS when weights vary.
Complexity roughly O(RC log RC) with a binary heap.
Question 2: count valid parentheses substrings
Q: Count substrings of a parentheses string that are valid.
Stack or DP: track last unmatched index. Variants ask longest valid length instead of count.
Watch empty string and all-closing cases.
Question 3: course schedule with prerequisites
Q: Given courses and prerequisite pairs, return a valid order or detect cycle.
Topological sort (Kahn BFS or DFS coloring). If cycle, return empty / impossible.
Classic Google-interview-adjacent graph problem that also appears in OA banks.
Question 4: median of two sorted arrays
Q: Find median of two sorted arrays in O(log (m+n)).
Binary search on partition. If you cannot finish optimally under time, state the O(m+n) merge approach first, then attempt the log solution if minutes remain.
Question 5: subarray sum equals k
Q: Count subarrays whose sum equals k.
Prefix sums + hash map of frequencies. O(n) average.
Negative numbers make sliding window invalid; prefer prefix hashing.
Question 6: design a tiny lru under coding constraints
Q: Implement get/put for capacity-k LRU cache.
Hash map + doubly linked list (or OrderedDict). OA versions may simplify to coding the eviction logic with clear tests.
Interviews will ask why list + map beats a single structure.
How to prepare for Google OA (8-week plan)
| Weeks | Focus | Exit criteria |
|---|---|---|
| 1-2 | Arrays, hashing, two pointers, sliding window | 40+ easy/medium solved cleanly |
| 3-4 | Trees, graphs (BFS/DFS), heaps | Can code BFS/DFS without notes |
| 5-6 | DP + greedy patterns (lean hard into graphs + DP) | 25+ medium DP/greedy with recursion to bottom-up |
| 7 | Timed full mocks matching Often 45-90 minutes for coding OA variants | Finish at least one hard and one medium with full tests with passing tests |
| 8 | Weak-topic repair + complexity review | Re-solve every miss within 48 hours |
Daily loop
- One timed medium problem (45-60 min hard cap)
- Write complexity and 3 edge cases before coding
- If stuck past 20 minutes, peek pattern name only, then re-solve tomorrow cold
- Log misses by topic on a simple sheet
Company pages on this site
- Google coding questions
- Google aptitude / mock quiz
- Google interview experience
- Google preparation guide
- Practice PDF: Google Placement Papers PDF (2026)
Common mistakes on Google OA
- Jumping into code without restating constraints and examples
- O(n^2) default when n is 1e5-scale
- No dry-run on a failing edge case before submit
- Weak second problem because you over-optimized the first for 40 minutes
- Ignoring interview communication practice after OA (Google loops are explanation-heavy)
Day-of checklist
- Stable internet, charged laptop, quiet room
- Confirm language template compiles on the platform before starting hard problems
- Skim all problems for 3-4 minutes, order by familiarity
- Submit a correct brute force early if constraints allow, then optimize
- Leave 8-10 minutes for edge-case tests you invent yourself