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First Working Interpreter

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First Working Interpreter

Hello everyone! I'm an undergrad in computer science in my last semester. I've tried my hand at a few interpreters the past year. This is my first one that I've actually got set up, with a working lexer and execution tactics. I've implemented the input and output prefixing primitives of the pi calculus. I intended to implement the replication and restriction primitives soon. I find process algebras very interesting. They seem to be an important area of research, to bring the computing ecosystem to a concurrent-first paradigm. This github project isn't much to look at currently; it's my first project of any substance. However, you might find the linked research papers interesting! Feel free to share criticisms, insights, or your favorite process algebra!

Visit productView on Hacker NewsOct 16, 2022
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Product HuntOn track for Day 1 leaderboard · Strong signals: computer · Missing: mac, agents, macos
83%83% 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: io · Missing: https docs, excited, just released
61%61% 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, podcasting
46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
37%37% 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
14%14% 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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