Software product-line evaluation in the large

Software product-line engineering is arguably one of the most successful methods for establishing large portfolios of software variants in an application domain. However, despite the benefits, establishing a product line requires substantial upfront investments into a software platform with a proper product-line architecture, into new software-engineering processes (domain engineering and application engineering), into business strategies with commercially successful product-line visions and financial planning, as well as into re-organization of development teams. Moreover, establishing a full-fledged product line is not always possible or desired, and thus organizations often adopt product-line engineering only to an extent that deemed necessary or was possible. However, understanding the current state of adoption, namely, the maturity or performance of product-line engineering in an organization, is challenging, while being crucial to steer investments. To this end, several measurement methods have been proposed in the literature, with the most prominent one being the Family Evaluation Framework (FEF), introduced almost two decades ago. Unfortunately, applying it is not straightforward, and the benefits of using it have not been assessed so far. We present an experience report of applying the FEF to nine medium- to large-scale product lines in the avionics domain. We discuss how we tailored and executed the FEF, together with the relevant adaptations and extensions we needed to perform. Specifically, we elicited the data for the FEF assessment with 27 interviews over a period of 11 months. We discuss experiences and assess the benefits of using the FEF, aiming at helping other organizations assessing their practices for engineering their portfolios of software variants.

Configuração de Algoritmos Genéticos Multiobjetivos para Otimização de Projeto de Arquitetura de Linha de Produto

Algoritmos de busca têm sido explorados com sucesso na otimização de projeto de Arquitetura de Linha de Produto de Software (PLA) na abordagem seminal chamada Multi-Objective Approach for Product-Line Architecture Design (MOA4PLA). Tal abordagem produz um conjunto de alternativas de projeto de PLA que melhora os diferentes fatores otimizados. Atualmente, o algoritmo utilizado nesta abordagem é o algoritmo NSGA-II (Non-dominated Sorting Genetic Algorithm II), um algoritmo genético multiobjetivo que otimiza várias propriedades simultaneamente. Apesar de resultados experimentais promissores, estudar a melhor combinação de configuração dos parâmetros do algoritmo genético é imprescindível para obter melhores resultados. Valores de referência para os parâmetros ainda não foram definidos para otimização de projeto de PLA porque este é um tópico de pesquisa incipiente. Nesse contexto, o objetivo deste trabalho é identificar os valores mais adequados para configurar o algoritmo NSGA-II para a otimização de projetos de PLA por meio de um estudo experimental. Uma análise quantitativa baseada no indicador de qualidade hypervolume e em testes estatísticos foi realizada para determinar o valor mais adequado para configurar cada parâmetro do algoritmo.

An Introductory Study on an Architecture-Based Software Product Line Test Generation Method

Architecture-based testing allows test engineers to focus on the structure of complicated software and the interactions between software components that constitute the architecture of a software product. By observing and controlling the connections and interactions between components of complex or large systems during software testing, architecture-based testing can detect and localize such faults at those locations. The complexity of software product line testing is high because an implementation under test contains variability given the different binding times and is used by multiple products. This paper introduces how architecture-based testing is applied to test generation for a software product line and examines the strengths of the proposed method against existing software product line testing methods. The paper also illustrates the use of product line architecture and architectural artifacts to generate product line interaction tests. It was found that architecture-based testing can be applied to software product line test generation by tailoring it to deal with variability and product-line specific processes. The results of a comparison with existing methods show that architecture-based software product line test generation provides better capabilities in terms of variability in the testing stage, the explicit formation and application of binding, test coverage, and architectural awareness.