Automatizing Software Cognitive Complexity Reduction

We model the cognitive complexity reduction of a method as an optimization problem where the search space contains all sequences of Extract Method refactoring opportunities. We then propose a novel approach that searches for feasible code extractions allowing developers to apply them, all in an automated way. This will allow software developers to make informed decisions while reducing the complexity of their code. We evaluated our approach over 10 open-source software projects and was able to fix 78% of the 1,050 existing cognitive complexity issues reported by SonarQube. We finally discuss the limitations of the proposed approach and provide interesting findings and guidelines for developers.Universidad de Málaga (grants B1-2020_01 and B4-2019-05) Project PID2020-116727RB-I00 funded by MCIN/AEI /10.13039/501100011033 Rubén Saborido was recipient of a Juan de la Cierva grant FJC2018-038537-I funded by MCIN/AEI /10.13039/501100011033. Javier Ferrer was supported by a postdoc grant (DOC/00488) funded by the Andalusian Ministry of Economic Transformation, Industry, Knowledge and Universities