Behavior Specification of Product Lines via Feature Models and UML Statecharts with Variabilities

2008 ◽  
Author(s):  
Ariel Gonzalez ◽  
Carlos Luna
Keyword(s):  
Feature Models ◽  
Product Lines ◽  
Behavior Specification

scholarly journals Optimal Assignment of Augmented Reality Tasks for Edge-Based Variable Infrastructures

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 28
Author(s):  
Angel Cañete ◽  
Mercedes Amor ◽  
Lidia Fuentes
Keyword(s):  
Energy Consumption ◽  
Augmented Reality ◽  
Energy Efficient ◽  
Optimal Allocation ◽  
Fog Computing ◽  
Network Congestion ◽  
Feature Models ◽  
Product Lines ◽  
Software Product ◽  
Edge Based

In the last few years, the number of devices connected to the Internet has increased considerably; so has the data interchanged between these devices and the Cloud, as well as energy consumption and the risk of network congestion. The problem can be alleviated by reducing communication between Internet-of-Things devices and the Cloud. Recent paradigms, such as Edge Computing and Fog Computing, propose to move data processing tasks from the Cloud to nearby devices to where data is produced or consumed. One of the main challenges of these paradigms is to cope with the heterogeneity of the infrastructures where tasks can be offloaded. This paper presents a solution for the optimal allocation of computational tasks to edge devices, with the aim of minimizing the energy consumption of the overall application. The heterogeneity is represented and managed by using Feature Models, widely employed in Software Product Lines. Given the application and infrastructure configurations, our Optimal Tasks Assignment Framework generates the optimal task allocation and resources assignment. The resultant deployment represents the most energy efficient configuration at load-time, without compromising the user experience. The scalability and energy saving of the approach are evaluated in the domain of augmented reality applications.

scholarly journals CyberSPL: A Framework for the Verification of Cybersecurity Policy Compliance of System Configurations Using Software Product Lines

2019 ◽  
Vol 9 (24) ◽  
pp. 5364 ◽  
Author(s):  
Ángel Jesús Varela-Vaca  ◽  
Rafael M. Gasca ◽  
Rafael Ceballos ◽  
María Teresa Gómez-López ◽  
Pedro Bernáldez Torres
Keyword(s):  
Automated Analysis ◽  
Software Product Lines ◽  
Product Line ◽  
Feature Models ◽  
Product Lines ◽  
Software Products ◽  
Wide Range ◽  
Proposal A ◽  
Software Product ◽  
Real Scenario

Cybersecurity attacks affect the compliance of cybersecurity policies of the organisations. Such disadvantages may be due to the absence of security configurations or the use of default configuration values of software products and systems. The complexity in the configuration of products and systems is a known challenge in the software industry since it includes a wide range of parameters to be taken into account. In other contexts, the configuration problems are solved using Software Product Lines. This is the reason why in this article the framework Cybersecurity Software Product Line (CyberSPL) is proposed. CyberSPL is based on a methodology to design product lines to verify cybersecurity policies according to the possible configurations. The patterns to configure the systems related to the cybersecurity aspects are grouped by defining various feature models. The automated analysis of these models allows us to diagnose possible problems in the security configurations, reducing or avoiding them. As support for this proposal, a multi-user and multi-platform solution has been implemented, enabling setting a catalogue of public or private feature models. Moreover, analysis and reasoning mechanisms have been integrated to obtain all the configurations of a model, to detect if a configuration is valid or not, including the root cause of problems for a given configuration. For validating the proposal, a real scenario is proposed where a catalogue of four different feature models is presented. In this scenario, the models have been analysed, different configurations have been validated, and several configurations with problems have been diagnosed.

Addressing Non-Functional Properties in Feature Models: A Goal-Oriented Approach

2014 ◽  
Vol 24 (10) ◽  
pp. 1439-1487 ◽  
Author(s):  
Mehdi Noorian ◽  
Mohsen Asadi ◽  
Ebrahim Bagheri ◽  
Weichang Du
Keyword(s):  
Functional Properties ◽  
Product Line ◽  
Feature Model ◽  
Software Systems ◽  
Feature Models ◽  
Target Domain ◽  
Product Lines ◽  
Software Products ◽  
Software Product ◽  
Goal Models

Software Product Line (SPL) engineering is a systematic reuse-based software development approach which is founded on the idea of building software products using a set of core assets rather than developing individual software systems from scratch. Feature models are among the widely used artefacts for SPL development that mostly capture functional and operational variability of a system. Researchers have argued that connecting intentional variability models such as goal models with feature variability models in a target domain can enrich feature models with valuable quality and non-functional information. Interrelating goal models and feature models has already been proposed in the literature for capturing non-functional properties in software product lines; however, this manual integration process is cumbersome and tedious. In this paper, we propose a (semi) automated approach that systematically integrates feature models and goal models through standard ontologies. Our proposed approach connects feature model and goal model elements through measuring the semantic similarity of their annotated ontological concepts. Our work not only provides the means to systematically interrelate feature models and goal models but also allows domain engineers to identify and model the role and significance of non-functional properties in the domain represented by the feature model.

scholarly journals Genetic programming for feature model synthesis: a replication study

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Andreea Vescan ◽  
Adrian Pintea ◽  
Lukas Linsbauer ◽  
Alexander Egyed
Keyword(s):  
Genetic Programming ◽  
Reverse Engineering ◽  
Feature Model ◽  
Programming Approach ◽  
Feature Models ◽  
Product Lines ◽  
Model Synthesis ◽  
Wide Range ◽  
Software Product ◽  
Two Parameters

AbstractSoftware Product Lines (SPLs) make it possible to configure a single system based on features in order to create many different variants and cater to a wide range of customers with varying requirements. This configuration space is often modeled using Feature Models (FMs). However, in practice, the SPL (and consequently the FM) is often created after a set of variants has already been created manually. Automating the task of reverse engineering a feature model that describes a set of variants makes the process of adopting an SPL easier. The genetic programming pipeline is a good fit for feature models and has been shown to produce good reverse engineering results. In this paper, we replicate the results of such an existing approach with a larger set of feature models and investigate the effects of various genetic programming parameters and operators on the results. The design of our replication experiments employs three perspectives: duplicate the exact conditions using various features models, study the interaction of two parameters of the genetic programming approach, and optimize the values for the population and generation parameters and for the mutation and crossover operators. Results reinforce the previously obtained outcome, the original study being confirmed. The relations between the number of features and number of generations, respectively number of features and size of populations were also investigated and best values based on obtained results are provided. The current study also aimed to optimize various parameters of the genetic programming approach, the interpretation of those experiments discovering concrete values.

scholarly journals Uma Linguagem de Modelagem de Domínio Específico para Linhas de Produto de Software Dinâmicas

2020 ◽  
Author(s):  
Helberth Borelli ◽  
Sérgio Teixeira de Carvalho
Keyword(s):  
Adaptive Systems ◽  
Development Time ◽  
Software Product Lines ◽  
Feature Models ◽  
Service Model ◽  
Product Lines ◽  
Software Products ◽  
Domain Specific ◽  
Software Product ◽  
Dynamic Software

Software Product Lines can be briefly defined as a family of productsthat share some commonalities. The feature models approach isused to represent the commonalities and variabilities among products.One possible way for the construction of these models is theuse of meta-models. However, the management of these features,traditionally performed at development time, is not sufficient forthe development of Adaptive Systems. One solution to this type ofdevelopment is the approach of Dynamic Software Product Lineswhich has as one of its aims to promote features input and outputat runtime allowing the product to be adapted after changes incontexts. This article proposes a Domain Specific Modelling Languagethat aims at modeling Dynamic Software Product Lines. Thislanguage describes dynamic adaptations promoted at runtime andthrough the use of the state machine approach. Such adaptations,based on state machines, must promote state features changes orfeatures exchanges at runtime, enabling these software products tomanage derivations in its life cycle. Our proposal was implementedwith the use of a Healthcare scenario and its development wasbased on the concept of the component service model.

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