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Empirical Software Engineering

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01-12-2022

Intensifying the search-based optimization of product line architectures with crossover operators

Authors: Diego Fernandes da Silva, Luiz Fernando Okada, Wesley K. G. Assunção, Thelma Elita Colanzi

Published in: Empirical Software Engineering | Issue 7/2022

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Abstract

The Product Line Architecture (PLA) is a crucial artifact for the development of Software Product Lines. However, PLA is a complex artifact to be designed due to its large size and the multiple conflicting properties that need to be considered to ensure its quality, requiring a great effort for the architect. PLA designing has been formulated as an optimization problem aiming at improving some architectural properties in order to maximize both the feature modularization and the relational cohesion, and to minimize the class coupling. This kind of problem was successfully solved by multi-objective evolutionary algorithm. Nevertheless, most of existing approaches optimize PLA designs without applying the crossover operator, one of the fundamental genetic operators. To overcome these limitations, this paper aims to intensify the search-based PLA design optimization by presenting three crossover operators. These operators were empirically evaluated in quantitative and qualitative studies using three well-studied PLA designs. The experiments were conducted with eight experimental configurations of NSGA-II in comparison with a baseline that uses only mutation operators. Empirical results showed that there are significant differences among the use of only mutation and mutation with crossover. Also, we observed that the crossover operators contributed to generate solutions with better feature modularization. Finally, we could see that the proposed operators complement each other, since the experiment that combines at least two of the proposed operators achieved better results.

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The supplementary material is available at: https://doi.org/10.5281/zenodo.6516279

Example of search string with synonyms and complementary keywords: (“Software Design” OR “Software Architecture”) AND (“Evolutionary Algorithm” OR “Genetic Algorithm”) AND (“Crossover” OR “Crossover Operator” OR “Recombination”)

Digital libraries commonly used for Software Engineering literature: IEEE Xplore, ACM Digital Library, Scopus, Springer Link, Engineering Village, and ScienceDirect.

Google Scholar indexes scholarly literature: https://scholar.google.com/

The value of H is inverted in COE, as we are interested in maximizing the cohesion and MOA4PLA minimizes all the objective functions.

https://github.com/otimizes/OPLA-Tool

The file of each PLA used to conduct the study is available at https://github.com/otimizes/OPLA-Tool/tree/master/plas

Results of the experimental calibration are available at https://doi.org/10.5281/zenodo.6516279

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The designs used in the qualitative analysis are available at https://doi.org/10.5281/zenodo.6516279.

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Title: Intensifying the search-based optimization of product line architectures with crossover operators
Authors: Diego Fernandes da Silva
Luiz Fernando Okada
Wesley K. G. Assunção
Thelma Elita Colanzi
Publication date: 01-12-2022
Publisher: Springer US
Published in: Empirical Software Engineering / Issue 7/2022
Print ISSN: 1382-3256
Electronic ISSN: 1573-7616
DOI: https://doi.org/10.1007/s10664-022-10198-3

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