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

Towards an aspect weaving BPEL engine

This position paper proposes the use of dynamic aspects and the visitor design pattern to obtain a highly configurable and extensible BPEL engine. Using these two techniques, the core of this infrastructural software can be customised to meet new requirements and add features such as debugging, execution monitoring, or changing to another Web Service selection policy. Additionally, it can easily be extended to cope with customer-specific BPEL extensions. We propose the use of dynamic aspects not only on the engine itself but also on the workflow in order to tackle the problems of Web Service hot deployment and hot fixes to long running processes. In this way, composing aWeb Service "on-the-fly" means weaving its choreography interface into the workflow

Context-aware adaptation in DySCAS

DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met

A Model-Based Approach to Managing Feature Binding Time in Software Product Line Engineering

Software Product Line Engineering (SPLE) is a software reuse paradigm for developing software products, from managed reusable assets, based on analysis of commonality and variability (C & V) of a product line. Many approaches of SPLE use a feature as a key abstraction to capture the C&V. Recently, there have been increasing demands for the provision of flexibility about not only the variability of features but also the variability of when features should be selected (i.e., variability on feature binding times). Current approaches to support variations of feature binding time mostly focused on ad hoc implementation mechanisms. In this paper, we first identify the challenges of feature binding time management and then propose an approach to analyze the variation of feature binding times and use the results to specify model-based architectural components for the product line. Based on the specification, components implementing variable features are parameterized with the binding times and the source codes for the components and the connection between them are generated

Probabilistic Model Checking for Energy Analysis in Software Product Lines

In a software product line (SPL), a collection of software products is defined by their commonalities in terms of features rather than explicitly specifying all products one-by-one. Several verification techniques were adapted to establish temporal properties of SPLs. Symbolic and family-based model checking have been proven to be successful for tackling the combinatorial blow-up arising when reasoning about several feature combinations. However, most formal verification approaches for SPLs presented in the literature focus on the static SPLs, where the features of a product are fixed and cannot be changed during runtime. This is in contrast to dynamic SPLs, allowing to adapt feature combinations of a product dynamically after deployment. The main contribution of the paper is a compositional modeling framework for dynamic SPLs, which supports probabilistic and nondeterministic choices and allows for quantitative analysis. We specify the feature changes during runtime within an automata-based coordination component, enabling to reason over strategies how to trigger dynamic feature changes for optimizing various quantitative objectives, e.g., energy or monetary costs and reliability. For our framework there is a natural and conceptually simple translation into the input language of the prominent probabilistic model checker PRISM. This facilitates the application of PRISM's powerful symbolic engine to the operational behavior of dynamic SPLs and their family-based analysis against various quantitative queries. We demonstrate feasibility of our approach by a case study issuing an energy-aware bonding network device.Comment: 14 pages, 11 figure

Using problem descriptions to represent variabilities for context-aware applications

This paper investigates the potential use of problem descriptions to represent and analyse variability in context-aware software products. By context-aware, we refer to recognition of changes in properties of external domains, which are recognised as affecting the behaviour of products. There are many reasons for changes in the operating environment, from fluctuating resources upon which the product relies, to different operating locations or the presence of objects. There is an increasing expectation for software intensivedevices to be context-aware which, in turn, adds further variability to problem description and analysis. However, we argue in this paper that the capture of contextual variability on current variability representations and analyses has yet to be explored. We illustrate the representation of this type of variability in a pilot study, and conclude with lessons learnt and an agenda for further work

Achieving Autonomic Web Service Compositions with Models at Runtime

Over the last years, Web services have become increasingly popular. It is because they allow businesses to share data and business process (BP) logic through a programmatic interface across networks. In order to reach the full potential of Web services, they can be combined to achieve specifi c functionalities. Web services run in complex contexts where arising events may compromise the quality of the system (e.g. a sudden security attack). As a result, it is desirable to count on mechanisms to adapt Web service compositions (or simply called service compositions) according to problematic events in the context. Since critical systems may require prompt responses, manual adaptations are unfeasible in large and intricate service compositions. Thus, it is suitable to have autonomic mechanisms to guide their self-adaptation. One way to achieve this is by implementing variability constructs at the language level. However, this approach may become tedious, difficult to manage, and error-prone as the number of con figurations for the service composition grows. The goal of this thesis is to provide a model-driven framework to guide autonomic adjustments of context-aware service compositions. This framework spans over design time and runtime to face arising known and unknown context events (i.e., foreseen and unforeseen at design time) in the close and open worlds respectively. At design time, we propose a methodology for creating the models that guide autonomic changes. Since Service-Oriented Architecture (SOA) lacks support for systematic reuse of service operations, we represent service operations as Software Product Line (SPL) features in a variability model. As a result, our approach can support the construction of service composition families in mass production-environments. In order to reach optimum adaptations, the variability model and its possible con figurations are verifi ed at design time using Constraint Programming (CP). At runtime, when problematic events arise in the context, the variability model is leveraged for guiding autonomic changes of the service composition. The activation and deactivation of features in the variability model result in changes in a composition model that abstracts the underlying service composition. Changes in the variability model are refl ected into the service composition by adding or removing fragments of Business Process Execution Language (WS-BPEL) code, which are deployed at runtime. Model-driven strategies guide the safe migration of running service composition instances. Under the closed-world assumption, the possible context events are fully known at design time. These events will eventually trigger the dynamic adaptation of the service composition. Nevertheless, it is diffi cult to foresee all the possible situations arising in uncertain contexts where service compositions run. Therefore, we extend our framework to cover the dynamic evolution of service compositions to deal with unexpected events in the open world. If model adaptations cannot solve uncertainty, the supporting models self-evolve according to abstract tactics that preserve expected requirements.Alférez Salinas, GH. (2013). Achieving Autonomic Web Service Compositions with Models at Runtime [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34672TESI