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by ThrowawayR2
1779 days ago
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> "There's a reason they've trained the model on Github repositories instead of, say, the Windows kernel driver tree." At least part of the reason has to be because only a tiny percentage of developers use C++, particularly the flavor of C++ that Visual Studio speaks, as opposed to Javascript, Python, etc. Moreover, kernel and driver code doesn't resemble boilerplate code used in desktop applications. Is this not obvious to the people who keep repeating this? |
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The C and C++ boilerplate Microsoft uses is very much relevant to any driver development or native applicationd development (if that still exists) for their platform. Their example code, MSDN snippets and documentation is very influential to anyone using C++ for Windows applications. Their COM+ libraries are even more relevant because they all live in user land.
There's also plenty of MS code that's written in other languages for platforms like Azure or UWP.
The there's the C and C++ code that's out there on Github. The C style of the Linux kernel, forked over and over, is completely useless for anyone developing network tools. The GTK or QT C++ files are useless for anyone writing wxWidgets code. The conventions, behaviours and style for the source code of libcurl and Linux are as distant from each other as Windows Explorer is from the NT kernel. Yet both have been taken into account by the mighty Algorithm.
How is my shitty early Android app, still written in Java, with clearly C#-inspired naming and almost PHP-like class structure more relevant to anyone than Microsoft's own code base? At least theirs is functional and useful.
"Nobody programs like Microsoft so the code examples is useless" is not an excuse, because you can apply it to almost every project on Github in some way. The machine learning is supposed to distinguish all of that, that's the entire point.