HYGAR: a hybrid genetic algorithm for software architecture recovery
Type :
Conference paper
Publication Status :
Published
Access :
restrictedAccess
Abstract
Genetic algorithms have been used for clustering modules of a software system in line with the modularity principle. The goal of these algorithms is to recover an architectural view in the form of a modular structural decomposition of the system. We discuss design decisions and variations in existing genetic algorithms devised for this purpose. We introduce HYGAR, a novel hybrid variant of existing algorithms. We apply HYGAR for software architecture recovery of 5 real systems and compare its effectiveness with respect to a baseline and a state-of-the-art hybrid algorithm. Results show that HYGAR outperforms these algorithms in maximizing the modularity of the obtained clustering.
Source :
SAC '22: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
Date :
2022
Publisher :
ACM
Collections
Share this page