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Learn C and its lower levels interactively, in the browser
Hacker NewsLearn C and its lower levels interactively, in the browser
I made a simple virtual machine that runs C in the browser.This project is made as an experiment to see if C can be learned easier if the lower level is covered in paralel. Sandbox: https://vasyop.github.io/miniC-hosting Tutorial part 1: https://vasyop.github.io/miniC-hosting/?0 More info: https://github.com/vasyop/miniC-hosting/blob/master/README.md Please support this project: https://github.com/vasyop/miniC-hosting/blob/master/support.md
Share cardActual performance
356points
33comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac · Missing: agents, macos, agent35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue15%15% 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, crypto7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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