Building reliable and maintainable Dynamic Software Product Lines: An investigation in the Body Sensor Network domain

Pessôa, Leonardo Antonio Monteiro; Fernandes, Paula; Castro, Thiago M.; Alves, Vander; Rodrigues, Genana N.; Carvalho, Hervaldo Sampaio

doi:10.1016/j.infsof.2017.02.002

Cited by 21 publications

(21 citation statements)

References 25 publications

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“…Merging these ideas with research in the medical domain makes it possible to create integrated devices for body parameters monitoring so called Body Sensor Networks (BSN). We illustrate the concepts of our approach throughout this work using the example of the Body Sensor Network proposed in [19,21]. As the cornerstone of this work is the improvement of context specification for dependability analysis, we have chosen the BSN example as for this system the dependability attributes are of highest importance due to health issues.…”

Section: Running Example: Body Sensor Networkmentioning

confidence: 99%

“…Hence the quality goals need to adjust according to each profile. The ranges of the sensors involved in the operationalization of the patient status was defined by a health expert and declaratively expressed in the aforementioned work [19]. Table 1 shows how the sensors' values relate to the context healthRisk.…”

Section: Running Example: Body Sensor Networkmentioning

confidence: 99%

“…A contextual goal model (CGM) represents the requirements as goals, ways to meet requirements as tasks, and factors that can affect the quality and behaviour of a system as contexts [4]. The CGM presented in Figure 1 depicts the goals to be achieved by the Body Sensor Network, which is meant to detect patient emergencies based on its monitored data [19,25]. The root goal is "G1: Detect Emergency", which is performed by the actor Body Sensor Network.…”

Section: Contextual Goal Modelsmentioning

confidence: 99%

“…We evaluate our approach on a simulated prototype version of a Body Sensor Network system (BSN) [19]. The results showed the ability of the approach to detect important and critical cases to take corrective actions.…”

Section: Introductionmentioning

confidence: 99%

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Enhancing context specifications for dependable adaptive systems: A data mining approach

Rodrigues

Knauss

et al. 2019

Information and Software Technology

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Context: Adaptive systems are expected to cater for various operational contexts by having multiple strategies in achieving their objectives and the logic for matching strategies to an actual context. The prediction of relevant contexts at design time is paramount for dependability. With the current trend on using data mining to support the requirements engineering process, this task of understanding context for adaptive system at design time can benefit from such techniques as well. Objective: The objective is to provide a method to refine the specification of contextual variables and their relation to strategies for dependability. This refinement shall detect dependencies between such variables, priorities in monitoring them, and decide on their relevance in choosing the right strategy in a decision tree. Method: Our requirements-driven approach adopts the contextual goal modelling structure in addition to the operationalization values of sensed information to map contexts to the system's behaviour. We propose a design time analysis process using a subset of data mining algorithms to extract a list of relevant contexts and their related variables, tasks, and/or goals. Results: We experimentally evaluated our proposal on a Body Sensor Network system (BSN), simulating 12 resources that could lead to a variability space of 4096 possible context conditions. Our approach was able to elicit subtle contexts that would significantly affect the service provided to assisted patients and relations between contexts, assisting the decision on their need, and priority in monitoring.

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Section: Running Example: Body Sensor Networkmentioning

confidence: 99%

Section: Running Example: Body Sensor Networkmentioning

confidence: 99%

Section: Contextual Goal Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhancing context specifications for dependable adaptive systems: A data mining approach

Rodrigues

Knauss

et al. 2019

Information and Software Technology

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“…To discuss our proposed methodology, we use the example of a Body Sensor Network (BSN) [20] throughout this paper. The main objective of the BSN is to keep track of a patient's health status, continuously classifying it into low, moderate, or high risk and, in the case of any anomaly, to send an emergency signal to a central unit.…”

Section: Example: Body Sensor Networkmentioning

confidence: 99%

A learning approach to enhance assurances for real-time self-adaptive systems

Rodrigues

Caldas

Rodrigues

et al. 2018

Proceedings of the 13th International Conference on Software Engineering for Adaptive and Self-Managing Systems

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The assurance of real-time properties is prone to context variability. Providing such assurance at design time would require to check all the possible context and system variations or to predict which one will be actually used. Both cases are not viable in practice since there are too many possibilities to foresee. Moreover, the knowledge required to fully provide the assurance for self-adaptive systems is only available at runtime and therefore difficult to predict at early development stages. Despite all the efforts on assurances for self-adaptive systems at design or runtime, there is still a gap on verifying and validating real-time constraints accounting for context variability. To fill this gap, we propose a method to provide assurance of self-adaptive systems, at design-and runtime, with special focus on real-time constraints. We combine off-line requirements elicitation and model checking with on-line data collection and data mining to guarantee the system's goals, both functional and non-functional, with fine tuning of the adaptation policies towards the optimization of quality attributes. We experimentally evaluate our method on a simulated prototype of a Body Sensor Network system (BSN) implemented in OpenDaVINCI. The results of the validation are promising and show that our method is effective in providing evidence that support the provision of assurance.

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Introduction to Smart Maintenance

Xing

Marwala

2017

Smart Maintenance for Human–Robot Interaction

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Building reliable and maintainable Dynamic Software Product Lines: An investigation in the Body Sensor Network domain

Cited by 21 publications

References 25 publications

Enhancing context specifications for dependable adaptive systems: A data mining approach

Enhancing context specifications for dependable adaptive systems: A data mining approach

A learning approach to enhance assurances for real-time self-adaptive systems

Introduction to Smart Maintenance

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