Extending UML Components to Develop Software Product-Line Architectures: Lessons Learned

Contieri, Antonio C.; Correia, Guilherme; Colanzi, Thelma Elita; Gimenes, Itana Maria de Souza; OliveiraJr, Edson; Ferrari, Sandra; Masiero, Paulo César; Garcia, Alessandro

doi:10.1007/978-3-642-23798-0_13

Cited by 22 publications

(5 citation statements)

References 5 publications

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“…The modeling in component-based development, referred to as component modeling, defines the standards for the composition, modeling and deployment mechanism for the implementations of components. The authors of [23,24] used UML annotations for component models while [25] developed their own modeling languages. The PROGRESS project [25] defines the component models in the domain of embedded systems and consists of two modeling layers to handle different kinds of operation, i.e., ProSys models the systems and subsystems while ProSave captures the data transfer and control flow between the components.…”

Section: Model-driven Developmentmentioning

confidence: 99%

Efficient Model-Driven Prototyping for Edge Analytics

Chaudhary,

Guevara,

Singh

et al. 2023

Electronics

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Software development cycles in the context of IoT! (IoT!) applications require the orchestration of different technological layers, and involve complex technical challenges. The engineering team needs to become experts in these technologies and time delays are inherent due to the cross-integration process because they face steep learning curves in several technologies, which leads to cost issues, and often to a resulting product that is prone to bugs. We propose a more straightforward approach to the construction of high-quality IoT applications by adopting model-driven technologies (DIME and Pyrus), that may be used jointly or in isolation. The presented use case connects various technologies: the application interacts through the EdgeX middleware platform with several sensors and data analytics pipelines. This web-based control application collects, processes and displays key information about the state of the edge data capture and computing that enables quick strategic decision-making. In the presented case study of a Stable Storage Facility (SSF), we use DIME to design the application for IoT connectivity and the edge aspects, MongoDB for storage and Pyrus to implement no-code data analytics in Python. We have integrated nine independent technologies in two distinct Low-code development environments with the production of seven processes and pipelines, and the definition of 25 SIBs in nine distinct DSLs. The presented case study is benchmarked with the platform to showcase the role of code generation and the reusability of components across applications. We demonstrate that the approach embraces a high level of reusability and facilitates domain engineers to create IoT applications in a low-code fashion.

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Section: Model-driven Developmentmentioning

confidence: 99%

Efficient Model-Driven Prototyping for Edge Analytics

Chaudhary,

Guevara,

Singh

et al. 2023

Electronics

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“…Subject PLA Designs. Three PLA designs were used in the empírical study: Arcade Game Maker (AGM) [37], Mobile Media (MM) [10] and BET [12]. AGM was cre- MM is a mobile application composed of features that handle with music, video, and photo for portable devices [42].…”

Section: Empirical Study Definitionmentioning

confidence: 99%

“…We used as baseline the state-of-the-art tool, namely OPLA-Tool, as it is the tool most related to ours. The PLA designs used in the experiments were extensively used in other studies [10,12,14,23]. We used the most used search-based algorithm [8], which was configured according to previous works [5,32,36].…”

Section: Threats To Validitymentioning

confidence: 99%

OPLA-Tool-ASP: a Tool to Prevent Architectural Smells in Search-based Product Line Architecture Design

Madrigar

Colanzi

Oizumi

et al. 2022

JSERD

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Search-based algorithms have been successfully employed in Product Line Architecture (PLA) design in the seminal approach named Multi-Objective Approach for Product-Line Architecture Design (MOA4PLA). This approach generates a set of alternative PLA designs, which optimize different architectural properties. In addition to these properties, the alternative PLA designs should have as few architectural smells as possible. Architectural smells can negatively impact PLA variability, PLA extensibility, SPL maintainability, and other non-functional attributes. However, one of the main findings of a previous study is that the tool that automates the application of MOA4PLA adversely introduces architectural smells in the automatically generated solutions. In this work, we present OPLA-Tool-ASP, which is a tool that implements guidelines to detect and prevent the architectural smells Unused Interface, Unused Brick, Concern Overload, and Link Overload in the context of MOA4PLA. An empirical study was carried out to assess the effectiveness of OPLA-Tool-ASP in preventing the aforementioned smells in the resulting PLA designs. The obtained results pointed out that the proposed tool is effective in both preventing the smells and improving the architectural properties selected for optimization.

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“…A Arquitetura de Linha de Produto (PLA)é um meio de garantir o reúso de uma LPS, pois ela envolve todos as características que são compartilhadas por todos os produtos que derivam de uma LPS [Contieri Jr et al 2011]. Trata-se de um projeto que contém todos os componentes e características possíveis, comuns e variáveis, a todos os produtos a serem derivados da LPS [Linden et al 2007].…”

Section: Projeto De Arquitetura De Linha De Produto De Software Baseaunclassified

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

Palioto¹,

Colanzi²

2020

Anais Da IV Escola Regional De Engenharia De Software (ERES 2020)

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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.

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Extending UML Components to Develop Software Product-Line Architectures: Lessons Learned

Cited by 22 publications

References 5 publications

Efficient Model-Driven Prototyping for Edge Analytics

Efficient Model-Driven Prototyping for Edge Analytics

OPLA-Tool-ASP: a Tool to Prevent Architectural Smells in Search-based Product Line Architecture Design

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

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