Chip-8 emulator in WebAssembly (JS –> WASM)

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I've been learning more about WebAssembly and a bucket list project I've always wanted to complete was to write an emulator. I chose the chip-8 vm as it's popular as a stepping stone project and pretty straight-forward. Only the display opcodes really gave me some trouble, specific to clipping/wrapping and tracking collisions. The demo includes some test roms as well as some roms from various octojams. The source is on GitHub. https://github.com/KevinBatdorf/chip8-wasm I orchestrated the project with TypeScript as I'm used to it and prefer the DX there, I created wrapper functions around the wasm op codes designed in a way similar to how you would write WebAssembly in wat format. So technically it's generated bytecode.

Visit product View on Hacker NewsJul 21, 2025

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

49%49% 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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

10%10% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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