Ben.Demystifier – more productive .NET exception traces

Hacker News

In .NET Exception.ToString() still outputs stack traces for C#1 so all the new features from C#2 -> C#7.2 come out as a garbled mess. Ben.Demystifier converts stack traces in the exceptions back into the source code signatures - rather than the compiler intermediary rosyln output methods. Particular highlights would be async noise, iterators, lamdbas and local functions. Feedback appreciated! GitHub: https://github.com/benaadams/Ben.Demystifier/ NuGet: https://www.nuget.org/packages/Ben.Demystifier/

Visit product View on Hacker NewsNov 11, 2017

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2points

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

59%59% 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 · Missing: plus, platform, intuitive

41%41% 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

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

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

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

Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos

34%34% 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

22%22% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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