Composition and Self-Adaptation of Service-Based Systems with Feature Models

The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932, TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Using Feature Models for Distributed Deployment in Extended Smart Home Architecture

Nowadays, smart home is extended beyond the house itself to encompass connected platforms on the Cloud as well as mobile personal devices. This Smart Home Extended Architecture (SHEA) helps customers to remain in touch with their home everywhere and any time. The endless increase of connected devices in the home and outside within the SHEA multiplies the deployment possibilities for any application. Therefore, SHEA should be taken from now as the actual target platform for smart home application deployment. Every home is different and applications offer different services according to customer preferences. To manage this variability, we extend the feature modeling from software product line domain with deployment constraints and we present an example of a model that could address this deployment challenge

A component-based product line architecture for workflow management systems

This paper presents a component-based product line for workflow management systems. The process followed to design the product line was based on the Catalysis method. Extensions were made to represent variability across the process. The domain of workflow management systems has been shown to be appropriate to the application of the product line approach as there are a standard architecture and models established by a regulatory board, the Workflow Management Coalition. In addition, there is a demand for similar workflow management systems but with some different features. The product line architecture was evaluated with Rapide simulation tools. The evaluation was based on selected scenarios, thus, avoiding implementation issues. The strategy that has been used to populate the architecture and experiment with the product line is shown. In particular, the design of the workflow execution manager component is described

A Product Line Systems Engineering Process for Variability Identification and Reduction

Software Product Line Engineering has attracted attention in the last two decades due to its promising capabilities to reduce costs and time to market through reuse of requirements and components. In practice, developing system level product lines in a large-scale company is not an easy task as there may be thousands of variants and multiple disciplines involved. The manual reuse of legacy system models at domain engineering to build reusable system libraries and configurations of variants to derive target products can be infeasible. To tackle this challenge, a Product Line Systems Engineering process is proposed. Specifically, the process extends research in the System Orthogonal Variability Model to support hierarchical variability modeling with formal definitions; utilizes Systems Engineering concepts and legacy system models to build the hierarchy for the variability model and to identify essential relations between variants; and finally, analyzes the identified relations to reduce the number of variation points. The process, which is automated by computational algorithms, is demonstrated through an illustrative example on generalized Rolls-Royce aircraft engine control systems. To evaluate the effectiveness of the process in the reduction of variation points, it is further applied to case studies in different engineering domains at different levels of complexity. Subject to system model availability, reduction of 14% to 40% in the number of variation points are demonstrated in the case studies.Comment: 12 pages, 6 figures, 2 tables; submitted to the IEEE Systems Journal on 3rd June 201

PuLSE-I: Deriving instances from a product line infrastructure

Reusing assets during application engineering promises to improve the efficiency of systems development. However, in order to benefit from reusable assets, application engineering processes must incorporate when and how to use the reusable assets during single system development. However, when and how to use a reusable asset depends on what types of reusable assets have been created.Product line engineering approaches produce a reusable infrastructure for a set of products. In this paper, we present the application engineering process associated with the PuLSE product line software engineering method - PuLSE-I. PuLSE-I details how single systems can be built efficiently from the reusable product line infrastructure built during the other PuLSE activities