Abstract: Software is always changed to accommodate environmental changes to preserve its existence. While changes happen to the software, the internal structure tends to decline in quality. The refactoring process is worth running to preserve the internal structure of the software. The decomposition process is a suitable refactoring process for Blob smell in class. It tried to split up the class based on the context in order to arrange it based on each responsibility. The previous approach has been implemented but still leaves problems. The optimum arrangement of class cannot be achieved using the previous approach. The genetic algorithm provides the search mechanism to find the optimum state based on the criterion stated at the beginning of the process. This paper presents the use of genetic algorithms to solve the design-level class decomposition problem. The paper explained several points, including the conversion from class to the chromosome construct, the fitness function calculation, selection, crossover, and mutation. The results show that the use of a genetic algorithm was able to solve the previous problems. The genetic algorithm can solve the local optimum problem from the previous approach. The increment of the fitness function of the study case proves it.

Bayu Priyambadha, Nobuya Takahashi and Tetsuro Katayama, “A Genetic Algorithm-based Approach for Design-level Class Decomposition” International Journal of Advanced Computer Science and Applications(IJACSA), 15(4), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150448

@article{Priyambadha2024,
title = {A Genetic Algorithm-based Approach for Design-level Class Decomposition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150448},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150448},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {4},
author = {Bayu Priyambadha and Nobuya Takahashi and Tetsuro Katayama}
}