  Source code reviews are manual, time-consuming, and expensive. Human
involvement should be focused on analyzing the most relevant aspects of the
program, such as logic and maintainability, rather than amending style, syntax,
or formatting defects. Some tools with linting capabilities can format code
automatically and report various stylistic violations for supported programming
languages. They are based on rules written by domain experts, hence, their
configuration is often tedious, and it is impractical for the given set of
rules to cover all possible corner cases. Some machine learning-based solutions
exist, but they remain uninterpretable black boxes. This paper introduces
STYLE-ANALYZER, a new open source tool to automatically fix code formatting
violations using the decision tree forest model which adapts to each codebase
and is fully unsupervised. STYLE-ANALYZER is built on top of our novel assisted
code review framework, Lookout. It accurately mines the formatting style of
each analyzed Git repository and expresses the found format patterns with
compact human-readable rules. STYLE-ANALYZER can then suggest style
inconsistency fixes in the form of code review comments. We evaluate the output
quality and practical relevance of STYLE-ANALYZER by demonstrating that it can
reproduce the original style with high precision, measured on 19 popular
JavaScript projects, and by showing that it yields promising results in fixing
real style mistakes. STYLE-ANALYZER includes a web application to visualize how
the rules are triggered. We release STYLE-ANALYZER as a reusable and extendable
open source software package on GitHub for the benefit of the community.
