Are MAs profitable to search‐based PLA design?. Issue 6 (1st December 2019)

• Record Type: Journal Article
• Authors: Choma Neto, João; da Silva Herculano, Cristiano; Elita Colanzi, Thelma; Malachini Miotto Amaral, Aline Maria
• Is Part Of: IET software. Volume 13:Issue 6(2019)
• Page Start: 587
• Page End: 599
• Publication Date: 2019-12-01
• Subjects: multi-agent systems -- search problems -- software architecture -- genetic algorithms -- program testing; MAs profitable -- search-based PLA design -- architectural properties -- product-line architecture design -- multiobjective genetic algorithms -- memetic algorithms -- GA -- local search -- global search process -- PLA design optimisation -- design patterns -- MA-based implementation -- PLA designs -- original PLA design; Computer software -- Periodicals; Software engineering -- Periodicals; 005.1
• DOI: 10.1049/iet-sen.2018.5318
• Languages: English
• ISSNs: 1751-8806

Abstract

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.