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Real-time profiler for C++ [video]

Hacker News

Real-time profiler for C++ [video]

Hello HN, For a while now, I've been working on a Visual Studio extension that enables you to see code execution and variables in real-time, directly in the VS editor. A couple months ago, I implemented a prototype of a "profiler" mode which shows how much time a line takes relatively to the entire function and since then, I have released it as an update to the extension you can use. The profiler is completely real-time, meaning that you can watch how the profile changes depending on what is going on in the application. The instrumentation is automatic and is applied to all lines in the function, which means that you will not miss samples, like you would in a call stack sampling profiler. A really big advantage is that you can also freely browse around the codebase and explore the profile deeper and deeper without ever having to start or stop profiling sessions and waiting for the data to be assembled. Each line gets brighter as its impact becomes larger on the function, which is very similiar to the design Visual Studio uses for its performance captures. Besides the line you can view its current function percentage and also how many times the line was executed in the function call. More detailed info like the precise time measurements can be viewed by hovering over the tooltip. The extension with the new profiler mode is available on the VS marketplace: https://marketplace.visualstudio.com/items?itemName=donadigo... (activate the mode in top VS menu -> Extensions -> D0 -> Live Profiler). If you want to follow the project or have questions, I'm always available in the Discord server here: https://discord.gg/PY6X3NMmuN and there's more info about the project on its website: https://d-0.dev/

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, visual, code · Missing: mac, agents, macos
92%92% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% predicted probability of success on Indie Hackers, 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
63%63% 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: video, month, way · Missing: mobile apps, ios, personal
53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
49%49% 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
13%13% 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.

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