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

A Requirement-centric Approach to Web Service Modeling, Discovery, and Selection

Service-Oriented Computing (SOC) has gained considerable popularity for implementing Service-Based Applications (SBAs) in a flexible\ud and effective manner. The basic idea of SOC is to understand users'\ud requirements for SBAs first, and then discover and select relevant\ud services (i.e., that fit closely functional requirements) and offer\ud a high Quality of Service (QoS). Understanding users’ requirements\ud is already achieved by existing requirement engineering approaches\ud (e.g., TROPOS, KAOS, and MAP) which model SBAs in a requirement-driven\ud manner. However, discovering and selecting relevant and high QoS\ud services are still challenging tasks that require time and effort\ud due to the increasing number of available Web services. In this paper,\ud we propose a requirement-centric approach which allows: (i) modeling\ud users’ requirements for SBAs with the MAP formalism and specifying\ud required services using an Intentional Service Model (ISM); (ii)\ud discovering services by querying the Web service search engine Service-Finder\ud and using keywords extracted from the specifications provided by\ud the ISM; and(iii) selecting automatically relevant and high QoS services\ud by applying Formal Concept Analysis (FCA). We validate our approach\ud by performing experiments on an e-books application. The experimental\ud results show that our approach allows the selection of relevant and\ud high QoS services with a high accuracy (the average precision is\ud 89.41%) and efficiency (the average recall is 95.43%)

Towards a flexible service integration through separation of business rules

Driven by dynamic market demands, enterprises are continuously exploring collaborations with others to add value to their services and seize new market opportunities. Achieving enterprise collaboration is facilitated by Enterprise Application Integration and Business-to-Business approaches that employ architectural paradigms like Service Oriented Architecture and incorporate technological advancements in networking and computing. However, flexibility remains a major challenge related to enterprise collaboration. How can changes in demands and opportunities be reflected in collaboration solutions with minimum time and effort and with maximum reuse of existing applications? This paper proposes an approach towards a more flexible integration of enterprise applications in the context of service mediation. We achieve this by combining goal-based, model-driven and serviceoriented approaches. In particular, we pay special attention to the separation of business rules from the business process of the integration solution. Specifying the requirements as goal models, we separate those parts which are more likely to evolve over time in terms of business rules. These business rules are then made executable by exposing them as Web services and incorporating them into the design of the business process.\ud Thus, should the business rules change, the business process remains unaffected. Finally, this paper also provides an evaluation of the flexibility of our solution in relation to the current work in business process flexibility research

Model-driven design, simulation and implementation of service compositions in COSMO

The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven support for service-oriented software development. In particular, it addresses how services and compositions of services can be designed, simulated and implemented. The support presented is part of a larger framework, called COSMO (COnceptual Service MOdelling). Whereas in previous work we reported on the conceptual support provided by COSMO, in this paper we proceed with a discussion of the practical support that has been developed. We show how reference models (model types) and guidelines (design steps) can be iteratively applied to design service compositions at a platform independent level and discuss what tool support is available for the design and analysis during this phase. Next, we present some techniques to transform a platform independent service composition model to an implementation in terms of BPEL and WSDL. We use the mediation scenario of the SWS challenge (concerning the establishment of a purchase order between two companies) to illustrate our application of the COSMO framework

SOA-Driven Business-Software Alignment

The alignment of business processes and their supporting application software is a major concern during the initial software design phases. This paper proposes a design approach addressing this problem of business-software alignment. The approach takes an initial business model as a basis in deriving refined models that target a service-oriented software implementation. The approach explicitly identifies a software modeling level at which software modules are represented as services in a technology-platformindependent way. This model-driven service-oriented approach has the following properties: (i) there is a forced alignment (consistency) between business processes and supporting applications; (ii) changes in the business environment can be traced to the application and vice versa, via model relationships; (iii) the software modules modeled as services have a high degree of autonomy; (iv) migration to new technology platforms can be supported through the platform independent software model

"How May I Help You?": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts

Given the increasing popularity of customer service dialogue on Twitter, analysis of conversation data is essential to understand trends in customer and agent behavior for the purpose of automating customer service interactions. In this work, we develop a novel taxonomy of fine-grained "dialogue acts" frequently observed in customer service, showcasing acts that are more suited to the domain than the more generic existing taxonomies. Using a sequential SVM-HMM model, we model conversation flow, predicting the dialogue act of a given turn in real-time. We characterize differences between customer and agent behavior in Twitter customer service conversations, and investigate the effect of testing our system on different customer service industries. Finally, we use a data-driven approach to predict important conversation outcomes: customer satisfaction, customer frustration, and overall problem resolution. We show that the type and location of certain dialogue acts in a conversation have a significant effect on the probability of desirable and undesirable outcomes, and present actionable rules based on our findings. The patterns and rules we derive can be used as guidelines for outcome-driven automated customer service platforms.Comment: 13 pages, 6 figures, IUI 201