Abstract
Refactoring large systems involves several sources of uncertainty related to the severity levels of code smells to be corrected and the importance of the classes in which the smells are located. Due to the dynamic nature of software development, these values cannot be accurately determined in practice, leading to refactoring sequences that lack robustness. To address this problem, we introduced a multiobjective robust model, based on NSGA-II, for the software refactoring problem that tries to find the best trade-off between quality and robustness.
Type
Publication
Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
Mohamed Wiem Mkaouer
Assistant Professor of Software Engineering
Research interests software refactoring and quality.
