i'm at a loss of words after reading a paper about reformatting code using an ML model that has a measured statistical quantity A_c which says how often the reformatted code behaves the same as the original

the "ideal" (their choice of words) case is 64.2%

edit: this got popular without me really intending to, so here's why i'm reading research: i want a semantic style transfer tool that can automatically format a patch "the same as the rest of the file / rest of codebase is formatted" without the rigidity involved in black or rustfmt that i find so hostile to my workflow that i refuse to use them. obviously, i want a tool that generates semantically equivalent code 100.0% of time (ignoring source locations or reading from __file__)

this isn't satire, this is real research published by IEEE/ACM

@whitequark So let me get this straight, IEEE thinks you should count it as a win if rewriting your code by vibing it has less than 15% better odds than a literal coinflip of reproducibility?

edited for clarity and to fix a typo

@disorderlyf @whitequark IEEE and ACM don't do the research nor they think you to do things, they are publishers that own journals and conferences where researchers publish their work
@urixturing @disorderlyf yeah. there are other issues with their models but this isn't one