Semantic Matching of Components at Run-Time in Distributed Environments

Criado, Javier; Iribarne, Luís; Padilla, Nicolás; Ayala, Rosa

doi:10.1007/978-3-319-26138-6_46

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…This step requires three inputs: the set of alternative software architectures (generated by the default model transformation process), a set of metrics to measure QAs and constraints, and the specification of the components to feed the metrics at run-time (stored in the component and architecture models [37,2]). It is noteworthy to clarify that all the required information to calculate the set of metrics must be allocated in these models.…”

Section: Step 2: Measuring Qas and Constraints At Run-timementioning

confidence: 99%

Quality-aware Architectural Model Transformations in Adaptive Mashups User Interfaces

Criado

Martínez‐Fernández

Ameller

et al. 2018

Self Cite

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Mashup user interfaces provides their functionality through the combination of different services. The integration of such services can be solved by using reusable and third-party components. Furthermore, these interfaces must be adapted to user preferences, context changes, user interactions and component availability. Model transformation is a useful mechanism to address this adaptation but normally these operations only focus on the functional requirements. In this sense, quality attributes should be included in the adaptation process to obtain the best adapted mashup user interface. This paper proposes a generic quality-aware transformation process to support the adaptation of software architectures. The transformation process has been applied in ENIA, a geographic information system, by constructing a specific quality model for the adaptation of mashup user interfaces. This model is taken into account for evaluating the different transformation alternatives and choosing the one that maximizes the quality assessments. The approach has been validated by a set of adaptation scenarios that are intended to maximize different quality factors and therefore apply distinct combinations of metrics.

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Section: Step 2: Measuring Qas and Constraints At Run-timementioning

confidence: 99%

Quality-aware Architectural Model Transformations in Adaptive Mashups User Interfaces

Criado

Martínez‐Fernández

Ameller

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…The metrics presented here are focused on our particular domain of component-based systems, but they can be adapted according to the needs. This step requires three inputs: the set of alternative software architectures (generated by the default model transformation process), a set of metrics to measure QAs and constraints (see Table 1 for QAs and Table 2 for constraints), and the specification of the components to feed the metrics at run-time (stored in the metamodel [8,10]). It is important to emphasize that Tables 1 and 2 show metrics elicited and validated by an expert in the domain architecture of component-based systems, but they may be adapted to the needs of other domains.…”

Section: Step 2: Measuring Qas and Constraints At Run-timementioning

confidence: 99%

Exploring Quality-Aware Architectural Transformations at Run-Time: The ENIA Case

Criado

Martínez‐Fernández

Ameller

et al. 2016

Model and Data Engineering

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Abstract. Adapting software systems at run-time is a key issue, especially when these systems consist of components used as intermediary for human-computer interaction. In this sense, model transformation techniques have a widespread acceptance as a mechanism for adapting and evolving the software architecture of such systems. However, existing model transformations often focus on functional requirements, and quality attributes are only manually considered after the transformations are done. This paper aims to improve the quality of adaptations and evolutions in component-based software systems by taking into account quality attributes within the model transformation process. To this end, we present a quality-aware transformation process using software architecture metrics to select among many alternative model transformations. Such metrics evaluate the quality attributes of an architecture. We validate the presented quality-aware transformation process in ENIA, a geographic information system whose user interfaces are based on coarsegrained components and need to be adapted at run-time.

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Semantic Matching of Components at Run-Time in Distributed Environments

Cited by 2 publications

References 14 publications

Quality-aware Architectural Model Transformations in Adaptive Mashups User Interfaces

Quality-aware Architectural Model Transformations in Adaptive Mashups User Interfaces

Exploring Quality-Aware Architectural Transformations at Run-Time: The ENIA Case

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