Problem Bank - 2,472 interview problems
Practice the problems
companies are actually asking.
Company-scoped practice from 241 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
2,472
practice problems
updated daily241
companies covered
updated daily59
topics covered
across all formats5
practice formats
coding - data - design - project241 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
485problems
5 formatsAlgorithms
GGoogle
125problems
2 formatsAlgorithms
TTiktok
114problems
1 formatAlgorithms
MMicrosoft
93problems
2 formatsAlgorithms
IIBM
86problems
1 formatAlgorithms
UUber
75problems
3 formatsAlgorithms
SSalesforce
69problems
2 formatsAlgorithms
SSnowflake
63problems
2 formatsAlgorithms
AAtlassian
60problems
1 formatAlgorithms
SStripe
54problems
2 formatsAlgorithms
OOpenAI
46problems
3 formatsAlgorithms
GGoldman Sachs
42problems
3 formatsAlgorithms
A run-through
Scope / Solve / Review.
Three minutes inside the bank.
company
StripeDoorDashAirtable+238
stage
assessmentphoneonsitedesign
difficulty
easymediumhard
format
algorithmdatadesignproject
12 matchedfrom 2,472
59 topics
Mapped to the skills companies actually ask.
Topic heat reflects its frequency across every practice format.
Array
844Greedy
526String
526Hash Table
511Sorting
431Simulation
408Dynamic Programming
280Math
275Binary Search
167Design
139Graph
139Matrix
135Sliding Window
132Prefix Sum
131Heap
116Two Pointers
110Consistency
107Depth First Search
86Breadth First Search
84Data Modeling
80Intervals
80Stack
78Tree
78Concurrency
69Bank 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.