Elyasi, MiladSimitcioğlu, Muhammed EsadSaydemir, AbdullahEkici, AliSözer, Hasan2023-07-132023-07-132022http://hdl.handle.net/10679/8498https://doi.org/10.1145/3477314.3507020Genetic 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.engrestrictedAccessconferenceObject1417142400094656410019410.1145/3477314.3507020Genetic algorithmsReverse engineeringSoftware architecture recoverySoftware modularitySoftware module clustering2-s2.0-85130329885