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I wrote a custom assembler for CHIP-8 in C++

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I wrote a custom assembler for CHIP-8 in C++

I'm writing a custom assembler for CHIP-8 and just finished adding support for the DB/.byte directive so I can embed sprites in the ROM and finally get something drawn on the screen. It SHOULD support all OG CHIP-8 instructions, but still a ton of rough edges that I'm ironing out. This is my first ever C++ project, just like the CHIP-8 emulator was my first ever C (and emudev) project. It's so satisfying to write assembly and have your program spit out a ROM that actually runs in the emulator you wrote. All code is written by me (a lot of it livestreaming) as evident by the quality, no AI.

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Product HuntOn track for Day 1 leaderboard · Strong signals: code · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
51%51% 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
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
28%28% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% 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.

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