Quality attributes and quality models for ambient assisted living software systems: A systematic mapping

Autor(es)

Garces, Lina ; Ampatzoglou, Apostolos ; Avgeriou, Paris ; Nakagaw, Elisa Yumi

• Tipo de documento: Artigo Científico
• Fonte: INFORMATION AND SOFTWARE TECHNOLOGY; v. 82, p. 121-138, FEB 2017.
• Citações Web of Science: 17

Resumo

Context: Ambient Assisted Living (AAL) has become an essential, multidisciplinary research topic, aiming at providing software systems and services that assist people in their everyday life activities. Considering the critical nature of AAL systems, several initiatives have already contributed to the improvement of their quality, by mainly focusing on their non-functional requirements. Despite the importance of quality assurance in AAL systems, there is a lack of a comprehensive analysis on how quality assurance is performed in such systems. This fact might in turn lead to an absence of standardization with regard to the quality assurance process of these systems. Objective: We provide a broad, detailed panorama about the state of the art on quality models (QMs) and quality attributes (QAs) that are important for the AAL domain. Method: We performed a Systematic Mapping (SM). We used six publication databases to cover all published material pertinent for our SM. We initially obtained 287 studies that were filtered based on a set of well-defined inclusion/exclusion criteria, resulting into a set of 27 studies that were used for exploring QAs for ML systems. Results: The most common QAs used in the development of ML systems were identified and defined. We also characterized important critical attributes for software systems in the AAL domain. Additionally, QAs for some ML sub-domains were defined. Furthermore, we investigated how QM\&QA have been defined, evaluated, and used in that domain. Finally, we offered an analysis of the maturity of the studies identified in our SM. Conclusion: It is necessary to develop a complete QM that: (i) defines all common QAs for AAL systems; (ii) considers variability of QAs among ML sub-domains; (iii) analyses dependences among QAs; (iv) offers indicators or metrics to measure QAs; and (v) offers means to assess and predict quality of AAL systems. (C) 2016 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 13/20317-9 - Arquitetura de referência para sistemas de healthcare supportive home
• Beneficiário: Lina María Garcés Rodríguez
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 15/19192-2 - Arquitetura de referência para sistemas de healthcare supportive home
• Beneficiário: Lina María Garcés Rodríguez
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
• Processo FAPESP: 14/02244-7 - SASoS: projeto arquitetural de sistemas de sistemas intensivos em software
• Beneficiário: Elisa Yumi Nakagawa
• Modalidade de apoio: Auxílio à Pesquisa - Regular