Crappy Correlations

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Post your correlation, but it better be funny damn it.

Note: Please keep it funny, and not political . There are plenty of other places on Lemmy to post more serious type of content.

This is a community just for some fun based on the spurious correlations website made by a university student.

https://www.tylervigen.com/spurious/random

I have no relation to him, but you can visit the link above and see any random correlation that you want.

You can make your own with no graphics or programming knowledge from imgflip here

If you do actually follow the link you will see not only the graph but an ai generated explanation and an AI scholarly paper that supports these correlations.

Who knows what is going to happen when the AIs pick up these hundreds of scholarly papers and put them in their training data. Anyone who wants to post a better blank graph can do so.

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Now we know what C stands for (i.imgur.com)

submitted 1 month ago by [email protected] to c/[email protected]

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[–] [email protected] 37 points 1 month ago (6 children)

I am curious how code quality is measured. Coverity metrics? Spelling errors? Bug reports? Sounds like bullshit.

[–] [email protected] 12 points 1 month ago (1 children)

I don't care enough to read through the whole thing, but some cursory searching brought up a reddit thread where a commenter found the original thesis:

Strehmel, J. (2022). Is there a Correlation between the Use of Swearwords and Code Quality in Open Source Code? [Bachelor’s Thesis, Institute of Theoretical Informatics]. https://cme.h-its.org/exelixis/pubs/JanThesis.pdf

[–] [email protected] 6 points 1 month ago

SoftWipe [30] is an open source tool and benchmark to assess, rate, and review scientific software written in C or C++ with respect to coding standard adherence. The coding standard adherence is assessed using a set of static and dynamic code analysers such as Lizard (https://github.com/terryyin/lizard) or the Clang address sanitiser (https://clang.llvm.org/). It returns a score between 0 (low adherence) and 10 (good adherence). In order to simplify our experimental setup, we excluded the compilation warnings, which require a difficult to automate compilation of the assessed software, from the analysis using the --exclude-compilation option.

If that means anything to you.

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