Train AI-era coding skill.

Students train for AI-era interviews. Educators run live classrooms. Hiring teams see how candidates actually build with AI.

[Students, Educators, Hiring teams]

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https://algoarena.net/practice/7800

Back to Practice

Problem List

15:35

Time Remaining

Hide Timer

Code

1# Starport Access Code
2import sys
3 
4data = sys.stdin.read().split()
5t = int(data[0])
6ptr = 1
7 
8for _ in range(t):
9    n = int(data[ptr])
10    s = data[ptr + 1]
11    ptr += 2
12 
13    possible = False
14    for i, ch in enumerate(s):
15        if ch == "8" and n - i == 11:
16            possible = True
17            break
18 
19    print("YES" if possible else "NO")

Ln 1, Col 23Spaces: 4

Test Result0/3 Passed (0%)

Testcase

Input

1
11
80011223388

Your Output

Pending...

Expected

YES

All 3 public test cases shown

Practice this problem

Product lanes

More ways to build real skill.

Compete is the student training lane. Classroom is concrete today. Assessments is in progress. AFK and Vibecoding Courses are labeled as early concepts, with enough shape to show where the product family is going.

Compete

Live battles, guided reps, and pressure without the noise.

Ranked 1v1 is the flagship, with Puzzle Rush, guided practice, and self-ghost personal-best races as supporting ways to train.

Explore Compete

https://algoarena.net/battle

Exit BattleLIVE RANKED

Battle Lobby

Finding you a worthy opponent...

Searching for opponent

Looking for someone near your skill level.

Problem difficulty is set from your ranked Elo and your opponent's when a match is found. No extra setup needed.

Elapsed

0:00

Ranked Elo band

1217-1267

Est. time remaining 00:20

Scanning for opponents in your skill range...

Classroom / Synced Live Room

Live CS teaching without the chaos.

Host algorithm quizzes, watch students answer in real time, and debrief the exact concepts that need attention.

Room code

A short code gets the room together.

Share the code on the projector and students join from any device in seconds.

Join card

Students join from their own screen.

Enter the code, pick a name, and land in the lobby, ready for the first question.

Explore Classroom

Join at algoarena.net/classroom

or enter code

CS2026

Game Settings

Questions

Time

10s to 20m per question

Topics: arrays, linked lists, strings

Players

2 joined

MCMaya Chenready

NPNoah Parkready

You are the host

https://algoarena.net/dashboard

Classroom

Host or join live sessions: games, assessments, and collaborative practice.

Enter code

CS2026

Assessments

Early access

Hiring signal for AI-era engineering.

Recruiter workflows for measuring how candidates plan, prompt, verify, and ship with AI in the loop.

Preview Assessments

https://algoarena.net/assessments/demo

Agentic assessment38:12 left

app.jsindex.html

main

1// app.js - contact form

2const form = document.querySelector("#contact-form");

3const statusNote = document.querySelector("#form-status");

6form.addEventListener("submit", (event) => {

7});

Agent

verification: behavior · code ·

AFK

Concept

Away From Keyboard building for owned projects.

Early concept for turning ideas into repos, exports, benchmarks, and real code you can take anywhere.

Preview AFK

AFK conceptconcept preview

Rena AFK

chat to app workspace

You

Build a tiny web app where students track daily algorithm practice and see streaks.

First pass ready

Scaffold Next.js dashboard

Add local progress storage

Generate streak card and goal list

Run smoke check

Rena

I built the first pass. The app has editable goals, a streak counter, and exportable project files.

arena-practice-app4 files

app/page.tsx+84

app/api/progress/route.ts+31

components/GoalCard.tsx+42

lib/storage.ts+18

npm run check

lint passed

preview ready

app/page.tsx

1export default function PracticeTracker() {

2 const goals = ["arrays", "graphs", "dp"];

4 return <main className="grid gap-4">

5 <StreakCard days={12} />

6 <GoalList goals={goals} />

7 <RunSummary accepted={8} />

8 </main>;

Browser previewlive

Practice Tracker

June sprint

12 day streak

accepted

topics

42m

focus

Arrays5/6

Graphs2/4

Dynamic programming1/3

Next suggested build: add reminders and weekly review.

Vibecoding Courses

Concept

Learn to code with words, not syntax.

A future course where learners prompt Rena in plain English, watch the assistant translate intent into steps, and discover real CS concepts.

Preview Vibecoding Courses Course waitlist

Vibecoding Courses001 to 050

Task 001live UI

pick

move

drop

first green ball, then nearest green box

Sequencing

Move the right objects in the right order.

Task 002live UI

only move the matching color

Precision

Say exactly what should happen next.

Task 003live UI

filter green

nearest box

repeat

repeat until no green objects remain

Optimization

Find the shortest repeatable plan.

Ask Rena

plain English to CS concepts

Learner

Move every green thing into the nearest matching box.

Rena

Great. That command has a loop, a condition, and a nearest-match rule hiding inside it.

Find green objects

Choose nearest box

Repeat until done

Verify every match

for each object -> if green -> nearest box -> move -> check

Product evidence

Rooted in real practice, classroom, and assessment work.

The strongest proof today is the product itself: a problem bank, live battle surface, classroom flow, assessment workspace, and the team roots behind them.

10,000+

Problems

curated CS practice items across the arena

Languages

from Python and JavaScript to C++, Rust, and Go

1,500+

Accounts

developers, students, and classrooms on the platform

2,300+

Matches played

1v1 battles vs players and bots, replayable keystroke-by-keystroke

Two kinds of proof

Algorithmic rigor meets AI-era work samples

We test both, and the combination is the point. Classic problem-solving and realistic agentic work, on one platform, instead of pretending one replaces the other.

Algorithmic rigor

Classic data structures & problem-solving, the way interviews still test it.

Ranked 1v1 battles
The Arena-90 problem set
Puzzle Rush & guided practice

AI-era work samples

Realistic agentic & project work. Can they actually ship with AI in the loop?

Agentic & project assessments
Browser-grounded evidence
Prompt / edit / test lineage

Interview-ready by design

Practice the patterns companies interview with

Our questions cover the algorithmic patterns commonly asked at companies like these.

GraphsHash mapsDP

ArraysHeapsIntervals

Sliding windowTreesProduct sense

BFSStringsDynamic programming

SimulationGreedyEdge cases

CachingQueuesStreams

Shortest pathHeapsMaps

BacktrackingGraphsSearch

ParsingSortingHash tables

MatricesStringsGeometry

GraphsUnion findRanking

SQL logicTreesRecursion

Ledger mathIdempotencyParsing

Bit opsArraysOptimization

Data modelingBFSSets

MathDPProbability

Start practicing the patterns

Company logos are shown for identification only. AlgoArena is not affiliated with or endorsed by these companies.

Loved by builders

What people say

Real feedback from developers, CS students, and people who have built with us.

I've been using AlgoArena to prep for my Tesla interview. It mocks a real, live interview where you're under time pressure, actually challenging someone, so it mimics the real thing way more than doing LeetCode yourself. And it's more than LeetCode. Puzzle Rush helped me brush up on general knowledge too. It was really helpful when I was interviewing. I ended up landing roles at Tesla, JP Morgan, and Google prepping this way.

Carson Lin

SWE Intern @ Tesla · CS @ Swarthmore

I interviewed at a Series A startup and the format was basically what AlgoArena trains you for. They didn't just test algorithms, they tested how I think about product and how well I use AI to build. That's how interviews actually work now. When I worked at Tesla and big techs, you're expected to use AI, no questions asked. AlgoArena is the only one I've found that actually measures the skill that matters today: how well you work with AI, not without it.

Jaehoon Son

Co-Founder, tryhermes.dev · CS & Math @ Swarthmore

AlgoArena feels quite different from other platforms, and it's really exciting to explore. This platform is very new and makes coding feel like a game. Competing with others and solving problems within a time limit really helps improve our speed and prepares us better for coding interviews. I also like that the questions are presented in a different and interesting way. The gamified interface makes the whole experience much more enjoyable and keeps me motivated to practice more.

Shaik Sariya Niyaz

Blockchain Intern, li2edu · CSE @ GPREC

Working on AlgoArena was a great experience. The team is building something genuinely focused on improving how people learn and practice problem solving. I especially liked the clarity of vision and the speed at which ideas were being tested and shipped. It's a strong foundation, and I'm excited to see how it evolves.

Yashwanth S

Founder, Startup Metric · CS @ ACE Engineering

I really enjoyed problem solving on AlgoArena. Practicing in a competitive environment makes the DSA journey more engaging.

Himanshu Singh

Java Backend Developer · MCA @ AKTU

Carson Lin

SWE Intern @ Tesla · CS @ Swarthmore

Jaehoon Son

Co-Founder, tryhermes.dev · CS & Math @ Swarthmore

Shaik Sariya Niyaz

Blockchain Intern, li2edu · CSE @ GPREC

Yashwanth S

Founder, Startup Metric · CS @ ACE Engineering

I really enjoyed problem solving on AlgoArena. Practicing in a competitive environment makes the DSA journey more engaging.

Himanshu Singh

Java Backend Developer · MCA @ AKTU

AlgoArena has transformed how I prepare for technical interviews. The platform's ranked 1v1 battles provide that real-world 'pressure' you can't get from standard coding sites. The AI-powered code analysis is a game-changer. It didn't just tell me my solution was wrong; it helped me understand the 'why' behind my logic errors. If you're serious about leveling up your DSA skills, this is the most interactive way to do it.

Nawin M S

Backend Developer · CSE @ Velammal

Legitimately stressful rushing to solve a LeetCode easy before your opponent. Fantastic interview prep. It definitely makes doing LeetCode problems more engaging and makes me try to finish them as fast as I can under pressure.

Griffin Young

Principal Scientist, Schrödinger · CS @ Stanford

AlgoArena has helped me manage my time better in solving logic puzzles, and it's a much less stressful resource than LeetCode. The practice interview helps me get a gauge at what a coding interview experience might look like, and helps me prep without having to memorize exactly what to say. It helps me build the tools for a successful interview.

Keyla Peralta

CS & Chinese @ Swarthmore

I like how easy it is to jump into practice. The platform feels well organized, and the UI is great. Great work on building it!

Yash Chaturvedi

Intern, DRDO · CSE @ MUJ

Nawin M S

Backend Developer · CSE @ Velammal

Griffin Young

Principal Scientist, Schrödinger · CS @ Stanford

Keyla Peralta

CS & Chinese @ Swarthmore

I like how easy it is to jump into practice. The platform feels well organized, and the UI is great. Great work on building it!

Yash Chaturvedi

Intern, DRDO · CSE @ MUJ

Stay close to the frontier.

Research, documentation, and benchmarks that explain how AlgoArena measures skill in the AI era.

Research and field notes

CS education, AI-era assessments, keystroke/process-signal ideas, and product notes from building in public.

Read field notes

Product notesMay to Jun

CS classroom study

How live coding challenges change practice, debrief, and participation.

Keystroke signals

Process traces for integrity, effort, and AI-era assessment evidence.

LLM build notes

What the prompting, review, and shipping process taught the team.

Platform documentation

Setup guides for Compete, Classroom, assessments, and how the platform fits together.

Open docs

Docs index

Compete

Classroom

Assessments

Vibecoding Courses

Classroom setup

Host a live algorithm session

Create quiz

Share room code

Review debrief

Benchmarks and evidence

The public direction for scoring, judging quality, and evidence that explains more than a pass/fail result.

Explore benchmarks

Evidence modelscoring notes

Tests

3/3

Process

clear

AI use

reviewed

Reviewer summary

Score should explain the path: prompt quality, edit ownership, test discipline, and final correctness.

Replay attached

Rubric notes

Product updates

Stay in the loop

Get updates as Assessments, AFK, and Vibecoding Courses move from concept to real product.

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FAQ

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