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Predicting Expert Now Evaluations in Software Code Reviews (arxiv.org)
2 points by telotortium on Nov 21, 2024 | hide | past | favorite | 1 comment


“””

I’m at Stanford and I research software engineering productivity.

We have data on the performance of >50k engineers from 100s of companies.

Inspired by @deedydas, our research shows:

~9.5% of software engineers do virtually nothing: Ghost Engineers (0.1x-ers)

“””

https://x.com/yegordb/status/1859290734257635439?s=46

Uses LLMs to build a classifier to evaluate the usefulness of commits on company-private Git repositories. The classifier has r=0.85 correlation with a 10-person panel of software engineer evaluators.




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