Context-aware Systems Testing and Validation

Augusto, Juan Carlos; Quinde, Mario; Oguego, Chimezie Leonard

doi:10.1109/dessert.2019.8770048

Cited by 6 publications

(7 citation statements)

References 22 publications

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“…The approaches based on user reviews (Atoum 2020;Jiang et al 2019;Leopairote et al 2013;Qian et al 2016) have the potential for generalization, but the adaptation process is not analyzed nor described. Also, (Augusto et al 2019) describes a generalizable approach, but it is oriented to test context aspects (of CASSs) specifically. iii.…”

Section: Discussionmentioning

confidence: 99%

“…This study considers three elements to represent the context (user profile, physical environment, platform) and quantifies metrics for the characteristics of SQuaRE in each context. Augusto et al (2019) describe a methodological approach to consider the context to derive the scenarios in which the system should be tested. The techniques that have been applied for context modeling include UML activity diagrams (Mirza and Khan 2018), formal methods (Djoudi et al 2016), based on bi-graphical reactive systems (Cherfia et al 2017) and context-aware flow graphs (Lu et al 2006).…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Towards automatic evaluation of the Quality-in-Use in context-aware software systems

Salomón¹,

Duque

Montaña

et al. 2022

J Ambient Intell Human Comput

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Context-aware systems adapt their services to the user’s intentions and environment to improve the user experience. However, how to evaluate the quality of these systems in terms of user perception and context recognition is still an open problem. Our goal in this work is to evaluate the Quality-in-Use (QinU) for context-aware software systems according to the ISO/IEC 25010 standard and in an automated manner. This evaluation is oriented to be model-based, with domain specification and log data as input, while quality metrics and representations of users’ behavior as output. In this process, we use probabilistic models to discover user patterns, heuristic metrics as QinU estimation, clustering techniques to obtain user profiles according to their QinU, and feature selection to identify relevant factors of context. We propose a framework for assessing the QinU in context-aware software systems called Framework for Assessing Quality-in-use of Software (FAQuiS). FAQuiS includes a set of models to represent all dimensions of context, a methodology to apply the quality analysis to any system, and a set of tools and metrics to support and automate the process. We seek to test the impact and ease of integration in the industry for this framework. A case study in a company allows us to validate the applicability in a real environment. We analyze the mechanisms that support the QinU evaluation in context-aware systems, the feasibility of the QinU quantification, and the suitability of the integration in companies. Compared to previous works, our proposal offers a novel data-driven approach with general-purpose and industrial viability. FAQuiS can be used as a solution to assess the QinU based on the ISO 25010 standard and the models of user behaviors in different contexts. This solution analyzes the context changes in the user interaction, can quantify the quality loss in these contexts, and does not require big efforts to be integrated into a software development process.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Towards automatic evaluation of the Quality-in-Use in context-aware software systems

Salomón¹,

Duque

Montaña

et al. 2022

J Ambient Intell Human Comput

View full text Add to dashboard Cite

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“…Previously, each element was subjected to basic software testing processes focusing more on reliability than, for example, performance, although that was taken into consideration. Also, as the work by Augusto et al points out [47], there are gaps in context testing in intelligent environments. The context is outside classical development testing, yet it is a crucial element of these sorts of systems.…”

Section: Wandering Behaviourmentioning

confidence: 99%

“…In this research various contexts for each ADL or behaviour and some action related to them (e.g. going out) were tested following the methodology proposed in [47]. Some AR assessment examples can be seen at the Figshare repository 6 .…”

Section: Wandering Behaviourmentioning

confidence: 99%

AnAbEL: towards empowering people living with dementia in ambient assisted living

Manuel

Augusto

Stewart

2020

Univ Access Inf Soc

Self Cite

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“…However, in Sect. 5, the system is tested as a whole using Context-aware systems testing validation (COATI) [14] approach to gather insights from the different users. The purpose of this step is to identify potential issues and benefits that may not be evident when the entire system is tested by different users.…”

Section: Introductionmentioning

confidence: 99%

A user-guided personalization methodology to facilitate new smart home occupancy

Ali

Augusto

Windridge

et al. 2022

Univ Access Inf Soc

Self Cite

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Smart homes are becoming increasingly popular in providing people with the services they desire. Activity recognition is a fundamental task to provide personalised home facilities. Many promising approaches are being used for activity recognition; one of them is data-driven. It has some fascinating features and advantages. However, there are drawbacks such as the lack of ability to providing home automation from the day one due to the limited data available. In this paper, we propose an approach, called READY (useR-guided nEw smart home ADaptation sYstem) for developing a personalised automation system that provides the user with smart home services the moment they move into their new house. The system development process was strongly user-centred, involving users in every step of the system’s design. Later, the user-guided transfer learning approach was introduced that uses an old smart home data set to enhance the existing smart home service with user contributions. Finally, the proposed approach and designed system were tested and validated in the smart lab that showed promising results.

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Context-aware Systems Testing and Validation

Cited by 6 publications

References 22 publications

Towards automatic evaluation of the Quality-in-Use in context-aware software systems

Towards automatic evaluation of the Quality-in-Use in context-aware software systems

AnAbEL: towards empowering people living with dementia in ambient assisted living

A user-guided personalization methodology to facilitate new smart home occupancy

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