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Source code reviews are manual, time-consuming, and expensive. Humaninvolvement should be focused on analyzing the most relevant aspects of theprogram, such as logic and maintainability, rather than amending style, syntax,or formatting defects. Some tools with linting capabilities can format codeautomatically and report various stylistic violations for supported programminglanguages. They are based on rules written by domain experts, hence, theirconfiguration is often tedious, and it is impractical for the given set ofrules to cover all possible corner cases. Some machine learning-based solutionsexist, but they remain uninterpretable black boxes. This paper introducesSTYLE-ANALYZER, a new open source tool to automatically fix code formattingviolations using the decision tree forest model which adapts to each codebaseand is fully unsupervised. STYLE-ANALYZER is built on top of our novel assistedcode review framework, Lookout. It accurately mines the formatting style ofeach analyzed Git repository and expresses the found format patterns withcompact human-readable rules. STYLE-ANALYZER can then suggest styleinconsistency fixes in the form of code review comments. We evaluate the outputquality and practical relevance of STYLE-ANALYZER by demonstrating that it canreproduce the original style with high precision, measured on 19 popularJavaScript projects, and by showing that it yields promising results in fixingreal style mistakes. STYLE-ANALYZER includes a web application to visualize howthe rules are triggered. We release STYLE-ANALYZER as a reusable and extendableopen source software package on GitHub for the benefit of the community.

STYLE-ANALYZER: fixing code style inconsistencies with interpretable unsupervised algorithms