Desktop application to explore WebAssembly modules

Hacker News

An as of now fairly simple desktop application for Windows, Mac, and Linux to view all the definitions comprising a WebAssembly module (use HNWAVV as a coupon code to download for free): https://thewaywarddeveloper.com/webassembly-visual-viewer No installation is required, if you don’t have a WebAssembly module around, here’s the Flate compression library written in Rust: https://unpkg.com/wasm-flate@0.1.11-alpha/dist/9eae6f5a6ee0cd2a3640.module.wasm Right now the decoding algorithm is the most straightforward, which means there’s plenty of room for optimization. I also have a lot of additional features in mind. All feedback is welcome.

Visit product View on Hacker NewsOct 6, 2019

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

72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

53%53% 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

39%39% 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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, visual, coding · Missing: agents, macos, agent

35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

11%11% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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