  Readability models and tools have been proposed to measure the effort to read
code. However, these models are not completely able to capture the quality
improvements in code as perceived by developers. To investigate possible
features for new readability models and production-ready tools, we aim to
better understand the types of readability improvements performed by developers
when actually improving code readability, and identify discrepancies between
suggestions of automatic static tools and the actual improvements performed by
developers. We collected 370 code readability improvements from 284 Merged Pull
Requests (PRs) under 109 GitHub repositories and produce a catalog with 26
different types of code readability improvements, where in most of the
scenarios, the developers improved the code readability to be more intuitive,
modular, and less verbose. Surprisingly, SonarQube only detected 26 out of the
370 code readability improvements. This suggests that some of the catalog
produced has not yet been addressed by SonarQube rules, highlighting the
potential for improvement in Automatic static analysis tools (ASAT) code
readability rules as they are perceived by developers.
