Model-driven semantic Web service composition

As the number of available Web services increases there is a growing demand to realise complex business processes by combining and reusing available Web services. The reuse and combination of services results in a composition of Web services that may also involve services provided in the Internet. With semantically described Web services, an automated matchmaking of capabilities can help identify suitable services. To address the need for semantically de-fined Web services, OWL-S and WSML have been proposed as competing semantic Web service languages. We show how the proposed semantic Web service languages can be utilized within a model-driven methodology for build-ing composite Web services. In addition we combine the semantic-based discovery with the support for processing QoS requirements to apply a ranking or a selection of the candidates. The methodology describes a process which guides the developer through four phases, starting with the initial modelling, and ending with a new composite service that can be deployed and published to be consumed by other users.

QoS-Based Service Provision Schemes and Plan Durability in Service Composition

Abstract. In service composition, quality of service is a major criterion for selecting services to collaborate in a process flow to satisfy a certain quality goal. This paper presents an approach for service composition which considers QoS-based service provision schemes and variability of the QoS when planning. The QoS of a service can be stated in terms of complex service provision schemes, e.g. its service cost is offered at different rates for different classes of processing time, or its partnership with another service gives a special class of QoS when they operate in the same plan. We also address that it is desirable for service planning to result in a plan that is durable and reusable since change in the plan, e.g. by deviation of the actual QoS, would incur overheads. Our planning approach takes into account these dynamic situations and is demonstrated by using the Estimation of Distribution Algorithm

Metaheuristic models for decision support in the software construction process

En la actualidad, los ingenieros software no solo tienen la responsabilidad de construir sistemas que desempe~nen una determinada funcionalidad, sino que cada vez es más importante que dichos sistemas también cumplan con requisitos no funcionales como alta disponibilidad, efciencia o seguridad, entre otros. Para lograrlo, los ingenieros se enfrentan a un proceso continuo de decisión, pues deben estudiar las necesidades del sistema a desarrollar y las alternativas tecnológicas existentes para implementarlo. Todo este proceso debe estar encaminado a la obtención de sistemas software de gran calidad, reutilizables y que faciliten su mantenimiento y modificación en un escenario tan exigente y competitivo. La ingeniería del software, como método sistemático para la construcción de software, ha aportado una serie de pautas y tareas que, realizadas de forma disciplinada y adaptadas al contexto de desarrollo, posibilitan la obtención de software de calidad. En concreto, el proceso de análisis y diseño del software ha adquirido una gran importancia, pues en ella se concibe la estructura del sistema, en términos de sus bloques funcionales y las interacciones entre ellos. Es en este momento cuando se toman las decisiones acerca de la arquitectura, incluyendo los componentes que la conforman, que mejor se adapta a los requisitos, tanto funcionales como no funcionales, que presenta el sistema y que claramente repercuten en su posterior desarrollo. Por tanto, es necesario que el ingeniero analice rigurosamente las alternativas existentes, sus implicaciones en los criterios de calidad impuestos y la necesidad de establecer compromisos entre ellos. En este contexto, los ingenieros se guían principalmente por sus habilidades y experiencia, por lo que dotarles de métodos de apoyo a la decisión representaría un avance significativo en el área. La aplicación de técnicas de inteligencia artificial en este ámbito ha despertado un gran interés en los últimos años. En particular, la inteligencia artificial ha encontrado en la ingeniería del software un ámbito de aplicación complejo, donde diferentes técnicas pueden ayudar a conseguir la semi-automatización de tareas tradicionalmente realizadas de forma manual. De la unión de ambas áreas surge la denominada ingeniería del software basada en búsqueda, que propone la reformulación de las actividades propias de la ingeniería del software como problemas de optimización. A continuación, estos problemas podrían ser resueltos mediante técnicas de búsqueda como las metaheurísticas. Este tipo de técnicas se caracterizan por explorar el espacio de posibles soluciones de una manera \inteligente", a menudo simulando procesos naturales como es el caso de los algoritmos evolutivos. A pesar de ser un campo de investigación muy reciente, es posible encontrar propuestas para automatizar una gran variedad de tareas dentro del ciclo de vida del software, como son la priorización de requisitos, la planifcación de recursos, la refactorización del código fuente o la generación de casos de prueba. En el ámbito del análisis y diseño de software, cuyas tareas requieren de creatividad y experiencia, conseguir una automatización completa resulta poco realista. Es por ello por lo que la resolución de sus tareas mediante enfoques de búsqueda debe ser tratada desde la perspectiva del ingeniero, promoviendo incluso la interacción con ellos. Además, el alto grado de abstracción de algunas de sus tareas y la dificultad de evaluar cuantitativamente la calidad de un diseño software, suponen grandes retos en la aplicación de técnicas de búsqueda durante las fases tempranas del proceso de construcción de software. Esta tesis doctoral busca realizar aportaciones significativas al campo de la ingeniería del software basada en búsqueda y, más concretamente, al área de la optimización de arquitecturas software. Aunque se están realizando importantes avances en este área, la mayoría de propuestas se centran en la obtención de arquitecturas de bajo nivel o en la selección y despliegue de artefactos software ya desarrollados. Por tanto, no existen propuestas que aborden el modelado arquitectónico a un nivel de abstracción elevado, donde aún no existe un conocimiento profundo sobre cómo será el sistema y, por tanto, es más difícil asistir al ingeniero. Como problema de estudio, se ha abordado principalmente la tarea del descubrimiento de arquitecturas software basadas en componentes. El objetivo de este problema consiste en abstraer los bloques arquitectónicos que mejor definen la estructura actual del software, así como sus interacciones, con el fin de facilitar al ingeniero su posterior análisis y mejora. Durante el desarrollo de esta tesis doctoral se ha explorado el uso de una gran variedad de técnicas de búsqueda, estudiando su idoneidad y realizando las adaptaciones necesarias para hacer frente a los retos mencionados anteriormente. La primera propuesta se ha centrado en la formulación del descubrimiento de arquitecturas como problema de optimización, abordando la representación computacional de los artefactos software que deben ser modelados y definiendo medidas software para evaluar su calidad durante el proceso de búsqueda. Además, se ha desarrollado un primer modelo basado en algoritmos evolutivos mono-objetivo para su resolución, el cual ha sido validado experimentalmente con sistemas software reales. Dicho modelo se caracteriza por ser comprensible y exible, pues sus componentes han sido diseñados considerando estándares y herramientas del ámbito de la ingeniería del software, siendo además configurable en función de las necesidades del ingeniero. A continuación, el descubrimiento de arquitecturas ha sido tratado desde una perspectiva multiobjetivo, donde varias medidas software, a menudo en con icto, deben ser simultáneamente optimizadas. En este caso, la resolución del problema se ha llevado a cabo mediante ocho algoritmos del estado del arte, incluyendo propuestas recientes del ámbito de la optimización de muchos objetivos. Tras ser adaptados al problema, estos algoritmos han sido comparados mediante un extenso estudio experimental con el objetivo de analizar la ifnuencia que tiene el número y la elección de las métricas a la hora de guiar el proceso de búsqueda. Además de realizar una validación del rendimiento de estos algoritmos siguiendo las prácticas habituales del área, este estudio aporta un análisis detallado de las implicaciones que supone la optimización de múltiples objetivos en la obtención de modelos de soporte a la decisión. La última propuesta en el contexto del descubrimiento de arquitecturas software se centra en la incorporación de la opinión del ingeniero al proceso de búsqueda. Para ello se ha diseñado un mecanismo de interacción que permite al ingeniero indicar tanto las características deseables en las soluciones arquitectónicas (preferencias positivas) como aquellos aspectos que deben evitarse (preferencias negativas). Esta información es combinada con las medidas software utilizadas hasta el momento, permitiendo al algoritmo evolutivo adaptar la búsqueda conforme el ingeniero interactúe. Dadas las características del modelo, su validación se ha realizado con la participación de ingenieros con distinta experiencia en desarrollo software, a fin de demostrar la idoneidad y utilidad de la propuesta. En el transcurso de la tesis doctoral, los conocimientos adquiridos y las técnicas desarrolladas también han sido extrapolados a otros ámbitos de la ingeniería del software basada en búsqueda mediante colaboraciones con investigadores del área. Cabe destacar especialmente la formalización de una nueva disciplina transversal, denominada ingeniería del software basada en búsqueda interactiva, cuyo fin es promover la participación activa del ingeniero durante el proceso de búsqueda. Además, se ha explorado la aplicación de algoritmos de muchos objetivos a un problema clásico de la computación orientada a servicios, como es la composición de servicios web.Nowadays, software engineers have not only the responsibility of building systems that provide a particular functionality, but they also have to guarantee that these systems ful l demanding non-functional requirements like high availability, e ciency or security. To achieve this, software engineers face a continuous decision process, as they have to evaluate system needs and existing technological alternatives to implement it. All this process should be oriented towards obtaining high-quality and reusable systems, also making future modi cations and maintenance easier in such a competitive scenario. Software engineering, as a systematic method to build software, has provided a number of guidelines and tasks that, when done in a disciplinarily manner and properly adapted to the development context, allow the creation of high-quality software. More speci cally, software analysis and design has acquired great relevance, being the phase in which the software structure is conceived in terms of its functional blocks and their interactions. In this phase, engineers have to make decisions about the most suitable architecture, including its constituent components. Such decisions are made according to the system requirements, either functional or non-functional, and will have a great impact on its future development. Therefore, the engineer has to rigorously analyse existing alternatives, their implications on the imposed quality criteria and the need of establishing trade-o s among them. In this context, engineers are mostly guided by their own capabilities and experience, so providing them with decision support methods would represent a signi cant contribution. The application of arti cial intelligent techniques in this area has experienced a growing interest in the last years. Particularly, software engineering represents a complex application domain to arti cial intelligence, whose diverse techniques can help in the semi-automation of tasks traditionally performed manually. The union of both elds has led to the appearance of search-based software engineering, which proposes reformulating software engineering activities as optimisation problems. For their resolution, search techniques like metaheuristics can be then applied. This type of technique performs an \intelligent" exploration of the space of candidate solutions, often inspired by natural processes as happens with evolutionary algorithms. Despite the novelty of this research eld, there are proposals to automate a great variety of tasks within the software lifecycle, such as requirement prioritisation, resource planning, code refactoring or test case generation. Focusing on analysis and design, whose tasks require creativity and experience, trying to achieve full automation is not realistic. Therefore, solving design tasks by means of search approaches should be oriented towards the engineer's perspective, even promoting their interaction. Furthermore, design tasks are also characterised by a high level of abstraction and the di culty of quantitatively evaluating design quality. All these aspects represent key challenges for the application of search techniques in early phases of the software construction process. The aim of this Ph.D. Thesis is to make signi cant contributions in search-based software engineering and, specially, in the area of software architecture optimisation. Although it is an area in which signi cant progress is being done, most of the current proposals are focused on generating low-level architectures or selecting and deploying already developed artefacts. Therefore, there is a lack of proposals dealing with architectural modelling at a high level of abstraction. At this level, engineers do not have a deep understanding of the system yet, meaning that assisting them is even more di cult. As case study, the discovery of component-based software architectures has been primary addressed. The objective for this problem consists in the abstraction of the architectural blocks, and their interactions, that best de ne the current structure of a software system. This can be viewed as the rst step an engineer would perform in order to further analyse and improve the system architecture. In this Ph.D. Thesis, the use of a great variety of search techniques has been explored. The suitability of these techniques has been studied, also making the necessary adaptations to cope with the aforementioned challenges. A rst proposal has been focused on the formulation of software architecture discovery as an optimisation problem, which consists in the computational representation of its software artefacts and the de nition of software metrics to evaluate their quality during the search process. Moreover, a single-objective evolutionary algorithm has been designed for its resolution, which has been validated using real software systems. The resulting model is comprehensible and exible, since its components have been designed under software engineering standards and tools and are also con gurable according to engineer's needs. Next, the discovery of software architectures has been tackled from a multi-objective perspective, in which several software metrics, often in con ict, have to be simultaneously optimised. In this case, the problem is solved by applying eight state-of-theart algorithms, including some recent many-objective approaches. These algorithms have been adapted to the problem and compared in an extensive experimental study, whose purpose is to analyse the in uence of the number and combination of metrics when guiding the search process. Apart from the performance validation following usual practices within the eld, this study provides a detailed analysis of the practical implications behind the optimisation of multiple objectives in the context of decision support. The last proposal is focused on interactively including the engineer's opinion in the search-based architecture discovery process. To do this, an interaction mechanism has been designed, which allows the engineer to express desired characteristics for the solutions (positive preferences), as well as those aspects that should be avoided (negative preferences). The gathered information is combined with the software metrics used until the moment, thus making possible to adapt the search as the engineer interacts. Due to the characteristics of the proposed model, engineers of di erent expertise in software development have participated in its validation with the aim of showing the suitability and utility of the approach. The knowledge acquired along the development of the Thesis, as well as the proposed approaches, have also been transferred to other search-based software engineering areas as a result of research collaborations. In this sense, it is worth noting the formalisation of interactive search-based software engineering as a cross-cutting discipline, which aims at promoting the active participation of the engineer during the search process. Furthermore, the use of many-objective algorithms has been explored in the context of service-oriented computing to address the so-called web service composition problem

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

Development of service-oriented architectures using model-driven development : a mapping study

Context: Model-Driven Development (MDD) and Service-Oriented Architecture (SOA) are two challenging research areas in software engineering. MDD is about improving software development whilst SOA is a service-based conceptual development style, therefore investigating the available proposals in the literature to use MDD when developing SOA may be insightful. However, no studies have been found with this purpose. Objective: This work aims at assessing the state of the art in MDD for SOA systems. It mainly focuses on: what are the characteristics of MDD approaches that support SOA; what types of SOA are supported; how do they handle non-functional requirements. Method: We conducted a mapping study following a rigorous protocol. We identified the representative set of venues that should be included in the study. We applied a search string over the set of selected venues. As result, 129 papers were selected and analysed (both frequency analysis and correlation analysis) with respect to the defined classification criteria derived from the research questions. Threats to validity were identified and mitigated whenever possible. Results: The analysis allows us to answer the research questions. We highlight: (1) predominance of papers from Europe and written by researchers only; (2) predominance of top-down transformation in software development activities; (3) inexistence of consolidated methods; (4) significant percentage of works without tool support; (5) SOA systems and service compositions more targeted than single services and SOA enterprise systems; (6) limited use of metamodels; (7) very limited use of NFRs; and (8) limited application in real cases. Conclusion: This mapping study does not just provide the state of the art in the topic, but also identifies several issues that deserve investigation in the future, for instance the need of methods for activities other than software development (e.g., migration) or the need of conducting more real case studies.Peer ReviewedPostprint (author's final draft

Quality-of-Service-Aware Service Selection in Mobile Environments

The last decade is characterized by the rise of mobile technologies (UMTS, LTE, WLAN, Bluetooth, SMS, etc.) and devices (notebooks, tablets, mobile phones, smart watches, etc.). In this rise, mobiles phones have played a crucial role because they paved the way for mobile pervasion among the public. In addition, this development has also led to a rapid growth of the mobile service/application market (Statista 2017b). As a consequence, users of mobile devices nowadays find themselves in a mobile environment, with (almost) unlimited access to information and services from anywhere through the Internet, and can connect to other people at any time (cf. Deng et al. 2016; Newman 2015). Additionally, modern mobile devices offer the opportunity to select the services or information that best fit to a user’s current context. In this regard, mobile information services support users in retrieving context and non-context information, such as about the current traffic situation, public transport options, and flight connections, as well as about real-world entities, such as sights, museums, and restaurants (cf. Deng et al. 2016; Heinrich and Lewerenz 2015; Ventola 2014). An example of the application of mobile information services is several users planning a joint city day trip. Here, the users could utilize information retrieved about real-world entities for their planning. Such a trip constitutes a process with multiple participating users and may encompass actions such as visiting a museum and having lunch. For each action, mobile information services (e.g., Yelp, TripAdvisor, Google Places) can help locate available alternatives that differ only in attributes such as price, average length of stay (i.e., duration), or recommendations published by previous visitors. In addition, context information (e.g., business hours, distance) can be used to more effectively support the users in their decisions. Moreover, because multiple users are participating in the same trip, some users want to or must conduct certain actions together. However, decision-makers (e.g., mobile users) attempting to determine the optimal solution for such processes – meaning the best alternative for each action and each participating user – are confronted with several challenges, as shown by means of the city trip example: First, each user most likely has his or her own preferences and requirements regarding attributes such as price and duration, which all must be considered. Furthermore, for each action of the day trip, a huge number of alternatives probably exist. Thus, users might face difficulties selecting the optimal alternatives because of an information overload problem (Zhang et al. 2009). Second, taking multiple users into account may require the coordination of their actions because of potential dependencies among different users’ tours, which, for example, is the case when users prefer to conduct certain actions together. This turns the almost sophisticated decision problem at hand into a problem of high complexity. The problem complexity is increased further when considering context information, because this causes dependencies among different actions of a user that must be taken into account. For instance, the distance to cover by a user to reach a certain restaurant depends on the location of the previously visited museum. In conclusion, it might be impossible for a user to determine an optimal city trip tour for all users, making decision support by an information system necessary. Because the available alternatives for each action of the process can be denoted as (information) service objects (cf. Dannewitz et al. 2008; Heinrich and Lewerenz 2015; Hinkelmann et al. 2013), the decision problem at hand is a Quality-of-Service (QoS)-aware service selection problem. This thesis proposes novel concepts and optimization approaches for QoS-aware service selection regarding processes with multiple users and context information, focusing on scenarios in mobile environments. In this respect, the developed multi user context-aware service selection approaches are able to deal with dependencies among different users’ service compositions, which result from the consideration of multiple users, as well as dependencies within a user’s service composition, which result from the consideration of context information. Consequently, these approaches provide suitable support for decision-makers, such as mobile users

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

Metodología dirigida por modelos para las pruebas de un sistema distribuido multiagente de fabricación

Las presiones del mercado han empujado a las empresas de fabricación a reducir costes a la vez que mejoran sus productos, especializándose en las actividades sobre las que pueden añadir valor y colaborando con especialistas de las otras áreas para el resto. Estos sistemas distribuidos de fabricación conllevan nuevos retos, dado que es difícil integrar los distintos sistemas de información y organizarlos de forma coherente. Esto ha llevado a los investigadores a proponer una variedad de abstracciones, arquitecturas y especificaciones que tratan de atacar esta complejidad. Entre ellas, los sistemas de fabricación holónicos han recibido una atención especial: ven las empresas como redes de holones, entidades que a la vez están formados y forman parte de varios otros holones. Hasta ahora, los holones se han implementado para control de fabricación como agentes inteligentes autoconscientes, pero su curva de aprendizaje y las dificultades a la hora de integrarlos con sistemas tradicionales han dificultado su adopción en la industria. Por otro lado, su comportamiento emergente puede que no sea deseable si se necesita que las tareas cumplan ciertas garantías, como ocurren en las relaciones de negocio a negocio o de negocio a cliente y en las operaciones de alto nivel de gestión de planta. Esta tesis propone una visión más flexible del concepto de holón, permitiendo que se sitúe en un espectro más amplio de niveles de inteligencia, y defiende que sea mejor implementar los holones de negocio como servicios, componentes software que pueden ser reutilizados a través de tecnologías estándar desde cualquier parte de la organización. Estos servicios suelen organizarse como catálogos coherentes, conocidos como Arquitecturas Orientadas a Servicios (‘Service Oriented Architectures’ o SOA). Una iniciativa SOA exitosa puede reportar importantes beneficios, pero no es una tarea trivial. Por este motivo, se han propuesto muchas metodologías SOA en la literatura, pero ninguna de ellas cubre explícitamente la necesidad de probar los servicios. Considerando que la meta de las SOA es incrementar la reutilización del software en la organización, es una carencia importante: tener servicios de alta calidad es crucial para una SOA exitosa. Por este motivo, el objetivo principal de la presente Tesis es definir una metodología extendida que ayude a los usuarios a probar los servicios que implementan a sus holones de negocio. Tras considerar las opciones disponibles, se tomó la metodología dirigida por modelos SODM como punto de partida y se reescribió en su mayor parte con el framework Epsilon de código abierto, permitiendo a los usuarios que modelen su conocimiento parcial sobre el rendimiento esperado de los servicios. Este conocimiento parcial es aprovechado por varios nuevos algoritmos de inferencia de requisitos de rendimiento, que extraen los requisitos específicos de cada servicio. Aunque el algoritmo de inferencia de peticiones por segundo es sencillo, el algoritmo de inferencia de tiempos límite pasó por numerosas revisiones hasta obtener el nivel deseado de funcionalidad y rendimiento. Tras una primera formulación basada en programación lineal, se reemplazó con un algoritmo sencillo ad-hoc que recorría el grafo y después con un algoritmo incremental mucho más rápido y avanzado. El algoritmo incremental produce resultados equivalentes y tarda mucho menos, incluso con modelos grandes. Para sacar más partidos de los modelos, esta Tesis también propone un enfoque general para generar artefactos de prueba para múltiples tecnologías a partir de los modelos anotados por los algoritmos. Para evaluar la viabilidad de este enfoque, se implementó para dos posibles usos: reutilizar pruebas unitarias escritas en Java como pruebas de rendimiento, y generar proyectos completos de prueba de rendimiento usando el framework The Grinder para cualquier Servicio Web que esté descrito usando el estándar Web Services Description Language. La metodología completa es finalmente aplicada con éxito a un caso de estudio basado en un área de fabricación de losas cerámicas rectificadas de un grupo de empresas español. En este caso de estudio se parte de una descripción de alto nivel del negocio y se termina con la implementación de parte de uno de los holones y la generación de pruebas de rendimiento para uno de sus Servicios Web. Con su soporte para tanto diseñar como implementar pruebas de rendimiento de los servicios, se puede concluir que SODM+T ayuda a que los usuarios tengan una mayor confianza en sus implementaciones de los holones de negocio observados en sus empresas