Un

Understanding sorting Algorithms

Hacker News

Understanding sorting Algorithms

I have created what I think is an effective Simulation for understanding the various sorting algorithms, it is the latest Sim listed on the home page: phyzixlabs.com Full disclosure. This is a port of : http://math.hws.edu/eck/jsdemo/sortlab.html Feedback is welcomed.

Share card

Actual performance

3points
2comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting
31%31% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: sde · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Co
Concurrent Sorting in Go61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Concurrent Sorting in Go

Hacker News4
Sl
Sleepsort – Sorting While Sleeping47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sleepsort – Sorting While Sleeping

Hacker News14
A
A sorting tutorial with runnable code47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A sorting tutorial with runnable code

Hacker News2
Un
Understanding the Bloch Sphere40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Understanding the Bloch Sphere

Hacker News7
So
Sorting Visualizations (with Audio)55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sorting Visualizations (with Audio)

Hacker News3
So
Sorting Algorithms Visualised with Audio49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Sorting Algorithms Visualised with Audio

Hacker News2
Vi
Visualize sorting algorithms53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Visualize sorting algorithms

Hacker News3
Fa
Fast(er) Sorting with Sorting Networks54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fast(er) Sorting with Sorting Networks

Hacker News28
Vi
Visualizing Sorting Algorithms with Sound58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Visualizing Sorting Algorithms with Sound

Hacker News5
Un
Understanding the Monty Hall paradox through code46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Understanding the Monty Hall paradox through code

Hacker News37