ReaperAI – Automatically delete dead code from your app

Hacker News

Hi all, We launched Reaper at the end of last year ( https://www.emergetools.com/blog/posts/dead-code-detection-w... ) with the goal of helping teams discover dead code in their mobile apps. Unlike typical static analysis that only finds technically unreachable code, Reaper is an SDK that monitors production data to discover code that's unused by real users (ex. stale feature flags). ReaperAI takes this a step further by actually being able to open pull requests in your repo to automatically delete the dead code that it finds. Here is a demo video: https://www.youtube.com/watch?v=y2FEaAmUvNw We're here to answer your questions & would love to hear any ideas or feedback you have!

Visit product View on Hacker NewsApr 25, 2024

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

82%82% 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

77%77% 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 · Strong signals: mobile apps, apps, video · Missing: ios, personal, entrepreneurs

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

39%39% 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

24%24% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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