FOSD – Framework of Operating System Development

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The FOSD(Framework for Operating System Development) Framework is an innovative and flexible framework for operating system development. It strives to provide flexible resources and tools to help developers design, develop, and deploy operating systems efficiently and effectively. The framework is intended to support various architectures and provide corresponding build systems that facilitate the overall development of the operating system. It gives the already-implemented build system for each architecture that can automatically detect and compile user's source code and create a full operating system with proper bootloader(that's suitable with architecture.) The framework also provides HAL(Hardware Abstraction Layer) that can remedy the difficulty of having to develop all the device drivers for every hardware. Although currently, we're in the early development stage of only having x86 architecture kernel that can barely print "Hello, world", we are planning to implement from the fundamental framework features like interrupt system or basic print system to the file system interface, complicated device drivers(corresponding to the architecture) or even feature for task management. The ultimate goal is to make the operating system development easy and efficient for everybody!

Visit product View on Hacker NewsAug 22, 2024

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

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface, efficient · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

12%12% 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.

Correct prediction on native model

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