Problem Bank - 3,756 interview problems
Practice the problems
companies are actually asking.
Company-scoped practice from 369 companies, spanning online assessments, phone screens, onsite interviews, system design, low-level design, and project coding.
Token-bucket rate limiter
Implement allow(ts) returning True if a request is permitted at unix ms ts for r req/s with burst up to b.
solution.pytests.txtnotes.mdpy 3.12 - 5.0ms
class RateLimiter: def __init__(self, r, b): self.r, self.b = r, b self.tokens, self.last = b, 0 def allow(self, ts): # refill since last call self.tokens = min(self.b, self.tokens + (ts - self.last) * self.r) self.last = ts return self.tokens >= 1
passbasic_one_req_per_sec0.4ms
passburst_5_then_refill1.1ms
passmonotonic_timestamps0.9ms
passedge_ts_equal_last0.6ms
4 / 4 passed - 3.0ms total+ custom test
3,756
practice problems
+1,172 / 30d369
companies covered
+120 / 30d59
topics covered
across all formats5
practice formats
coding - data - design - project369 companies
Browse by the company you are applying to.
Every problem is tagged with company and cohort, so practice follows your target list instead of a generic topic shuffle.
AAmazon
622problems
5 formatsAlgorithms
GGoogle
166problems
4 formatsAlgorithms
MMicrosoft
141problems
3 formatsAlgorithms
TTiktok
123problems
2 formatsAlgorithms
GGoldman Sachs
106problems
4 formatsAlgorithms
IIBM
105problems
3 formatsAlgorithms
SSalesforce
101problems
3 formatsAlgorithms
UUber
92problems
3 formatsAlgorithms
SSnowflake
74problems
2 formatsAlgorithms
OOpenAI
70problems
4 formatsAlgorithms
SStripe
68problems
2 formatsAlgorithms
AAtlassian
62problems
2 formatsAlgorithms
A run-through
Scope / Solve / Review.
Three minutes inside the bank.
company
StripeDoorDashAirtable+366
stage
assessmentphoneonsitedesign
difficulty
easymediumhard
format
algorithmdatadesignproject
12 matchedfrom 3,756
59 topics
Mapped to the skills companies actually ask.
Topic heat reflects its frequency across every practice format.
Array
1,309Hash Table
803String
744Simulation
698Sorting
609Greedy
607Dynamic Programming
389Math
386Design
293Graph
272Consistency
252Matrix
245Binary Search
218Data Modeling
186Depth First Search
185Heap
182Sliding Window
181Two Pointers
178Breadth First Search
173Concurrency
172Prefix Sum
167Tree
161Storage
147Stack
130Bank to Signal
The bank knows what is being asked right now.
When tracked inboxes start seeing Stripe OAs land, the Q3 set surfaces to the top. You practice this quarter's questions, not the ones that were popular in 2019.
- Problems get a HOT mark when an OA spikes in tracked inboxes.
- Each company set is dated and prioritized by freshness.
- Frozen cohorts drop in priority so you do not waste reps.
Stripe+12.4%promoted Q3 set47 pr
DoorDash+8.1%added 4 new problems32 pr
Anthropic+6.2%new cohort opened18 pr
Airtable+3.0%refreshed test cases28 pr
Adobe-2.1%lowered priority22 pr
Teslafrozenarchived19 pr
auto-curated - refreshed hourly
FastPrep vs generic banks
Practice by target, not by folklore.
| FastPrep | Generic question banks | |
|---|---|---|
| Company cohort tagging | Y | ~ |
| Runnable editor + inspectable tests | Y | ~ |
| Hiring-signal prioritization | Y | - |
| Post-pass approach review | Y | ~ |
Practice the set before it hits you.
Open the bank, pick your target company, and run the exact style of OA you are likely to see this week.