Predicting Expert Now Evaluations in Software Code Reviews
arxiv.org
arxiv.org
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.