RT Journal Article
T1 Automatizing Software Cognitive Complexity Reduction
A1 Saborido Infantes, Rubén
A1 Ferrer-Urbano, Francisco Javier
A1 Chicano-García, José-Francisco
A1 Alba-Torres, Enrique
K1 Ingeniería del software
AB 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.
PB IEEE Access
SN 2169-3536
YR 2022
FD 2022-01-20
LK https://hdl.handle.net/10630/23738
UL https://hdl.handle.net/10630/23738
LA eng
NO R. Saborido, J. Ferrer, F. Chicano and E. Alba, "Automatizing Software Cognitive Complexity Reduction," in IEEE Access, vol. 10, pp. 11642-11656, 2022, doi: 10.1109/ACCESS.2022.3144743.
NO Universidad de Málaga (grants B1-2020_01 and B4-2019-05)Project PID2020-116727RB-I00 funded by MCIN/AEI /10.13039/501100011033Rubén 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.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026