Problem Bank - 4,280 interview problems
Practice the problems
companies are actually asking.
Company-scoped practice from 392 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
4,280
practice problems
+1,444 / 30d392
companies covered
+133 / 30d59
topics covered
across all formats5
practice formats
coding - data - design - project392 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
688problems
5 formatsAlgorithms
GGoogle
266problems
4 formatsAlgorithms
MMicrosoft
155problems
3 formatsAlgorithms
TTikTok
123problems
2 formatsAlgorithms
IIBM
108problems
3 formatsAlgorithms
SSalesforce
108problems
3 formatsAlgorithms
GGoldman Sachs
107problems
4 formatsAlgorithms
UUber
95problems
3 formatsAlgorithms
SSnowflake
77problems
2 formatsAlgorithms
OOpenAI
70problems
4 formatsAlgorithms
SStripe
70problems
2 formatsAlgorithms
AAtlassian
64problems
2 formatsAlgorithms
A run-through
Scope / Solve / Review.
Three minutes inside the bank.
company
StripeDoorDashAirtable+389
stage
assessmentphoneonsitedesign
difficulty
easymediumhard
format
algorithmdatadesignproject
12 matchedfrom 4,280
59 topics
Mapped to the skills companies actually ask.
Topic heat reflects its frequency across every practice format.
Array
1,512Hash Table
924String
843Simulation
796Sorting
686Greedy
644Dynamic Programming
448Math
429Design
335Graph
319Consistency
293Matrix
276Binary Search
247Depth First Search
225Data Modeling
224Heap
210Two Pointers
209Breadth First Search
208Concurrency
203Sliding Window
194Tree
191Prefix Sum
179Storage
179Stack
154Bank 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.