Are MAs profitable to search-based PLA design?

Author(s)

Choma Neto, Joao ^[1] ; da Silva, Cristiano Herculano ^[1] ; Colanzi, Thelma Elita ^[1] ; Malachini Miotto Amaral, Aline Maria ^[1]

Affiliation

^[1] Univ Estadual Maringa, Dept Informat, Av Colombo 5790, Maringa, Parana - Brazil

• Document type: Journal article
• Source: IET Software; v. 13, n. 6, p. 587-599, DEC 2019.
• Web of Science Citations: 0

Abstract

The architectural properties of product-line architecture (PLA) design have been successfully optimised by multi-objective genetic algorithms (GAs). Memetic algorithms (MAs) extend GA by adding a local search after the global search process. MA outperformed GA in the context of class modelling, software testing and the next release problem. However, no studies on the application of MAs for PLA design optimisation were found in the literature. In light of this, the authors performed an exploratory study, where MA was used to apply design patterns for a search-based PLA design (SBPD) and achieved promising results. From the obtained results, they adjusted the MA-based implementation. This study aims at investigating if the MA is more profitable to SBPD than GAs. Two empirical studies that involve four PLA designs were carried out for this task by varying the pair of objective functions. Empirical results show that MA achieved satisfactory solutions, despite being influenced by the original PLA design. (AU)

• FAPESP's process: 14/03389-9 - Supporting mechanisms to the design and development of mobile learning environments and applications
• Grantee: Ellen Francine Barbosa
• Support Opportunities: Regular Research Grants