Semantic Model Alignment for Business Process Integration

Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects

ICSEA 2022: the seventeenth international conference on software engineering advances

The Seventeenth International Conference on Software Engineering Advances (ICSEA 2022), held between October 16th and October 20th, 2022, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. Several tracks were proposed to treat the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learned. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. Other advanced aspects are related to on-time practical aspects, such as run-time vulnerability checking, rejuvenation process, updates partial or temporary feature deprecation, software deployment and configuration, and on-line software updates. These aspects trigger implications related to patenting, licensing, engineering education, new ways for software adoption and improvement, and ultimately, to software knowledge management. There are many advanced applications requiring robust, safe, and secure software: disaster recovery applications, vehicular systems, biomedical-related software, biometrics related software, mission critical software, E-health related software, crisis-situation software. These applications require appropriate software engineering techniques, metrics and formalisms, such as, software reuse, appropriate software quality metrics, composition and integration, consistency checking, model checking, provers and reasoning. The nature of research in software varies slightly with the specific discipline researchers work in, yet there is much common ground and room for a sharing of best practice, frameworks, tools, languages and methodologies. Despite the number of experts we have available, little work is done at the meta level, that is examining how we go about our research, and how this process can be improved. There are questions related to the choice of programming language, IDEs and documentation styles and standard. Reuse can be of great benefit to research projects yet reuse of prior research projects introduces special problems that need to be mitigated. The research environment is a mix of creativity and systematic approach which leads to a creative tension that needs to be managed or at least monitored. Much of the coding in any university is undertaken by research students or young researchers. Issues of skills training, development and quality control can have significant effects on an entire department. In an industrial research setting, the environment is not quite that of industry as a whole, nor does it follow the pattern set by the university. The unique approaches and issues of industrial research may hold lessons for researchers in other domains. We take here the opportunity to warmly thank all the members of the ICSEA 2022 technical program committee, as well as all the reviewers. The creation of such a high-quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and effort to contribute to ICSEA 2022. We truly believe that, thanks to all these efforts, the final conference program consisted of top-quality contributions. We also thank the members of the ICSEA 2022 organizing committee for their help in handling the logistics of this event. We hope that ICSEA 2022 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in software engineering advances

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

MINERVA : Model drIveN and sErvice oRiented framework for the continuous improVement of business process & relAted tools

Organizations are facing several challenges nowadays, one of the most important ones being their ability to react quickly to changes either to their business process (BP) models or to the software implementing them. These changes can come from different sources: external requirements from partners or the market, or new internal requirements for the way that things are carried out by the defined BPs; they may also arise from improvement opportunities detected for the BPs defined, based on BPs execution monitoring and execution evaluation that is done by the organization, and/or its partners and customers. The increasing complexity of both BPs models and the software implementing them, requires the changes needed or the improvements to be carefully weighed against the impact their introduction will have; they ought also to be carried out in a systematic way to assure a successful development. Two key elements are to provide these requirements: the separation of BPs definition from their implementation to minimize the impact of changes in one to the other, and a process to introduce the changes or improvements in the existing BPs and/or software implementing them. Business Process Management (BPM) provides the means for guiding and supporting the modeling, implementation, deployment, execution and evaluation of BPs in an organization, based on the BP lifecycle. The realization of BPs by means of services provides the basis for separating their definition from the technologies implementing them and helps provide a better response to changes in either of the layers defined -definition and implementation of business processes- with minimum impact on the other. Modeling of both BP and services is a key aspect to support this vision, helping provide traceability between elements from one area to the other, so easing the analysis of the impact of changes, among other things. Models have proven to play an important role in the software development process, one of its key uses in the context of BP realization by means of services is that of designing services at a more abstract level than with specific technologies, also promoting reuse by separating services logic from its implementation. MINERVA: Model drIveN & sErvice oRiented framework for the continuous business process improVement & relAted tools is the framework that has been defined in this thesis work; it takes into account all the aspects mentioned, in which the SOC and MDD paradigms are applied to BPs focusing on their continuous improvement, extending an existing BP lifecycle with explicit execution measurement and improvement activities and elements. It is made up of three dimensions: i) conceptual, which defines the concepts that are managed throughout the framework. ii) methodological, which defines a methodology for service oriented development from BPs with automatic generation of SoaML service models from BPMN2 models, along with a continuous improvement process based on execution measurement of the occurrences of BPs in the organization to carry out the improvement effort. iii) tools support for the whole proposal based on several existing tools we have integrated, along with new ones we have developed. The proposals in MINERVA have been validated by means of an experiment and two case studies carried out in the context of real projects in two organizations, from which, as the main result of the applications performed, it can be concluded that MINERVA can be a useful and key guide for the continuous improvement of BPs realized by services and for the development of service oriented systems from BPs, with automatic generation of service models from BP models.Las organizaciones se enfrentan en la actualidad a varios retos, siendo uno de los más importantes su capacidad para reaccionar rápidamente a los cambios ya sea en sus modelos de procesos de negocio (PN) o en el software que los implementa. Estos cambios pueden provenir de distintas fuentes: requisitos externos de socios o del mercado, o nuevos requisitos internos para la forma en que las cosas se llevan a cabo por los PNs definidos; también pueden surgir de las oportunidades de mejora detectadas para los PNs definidos, en base al monitoreo y evaluación de la ejecución de los PNs llevada a cabo por la organización, y/o sus socios y clientes. La creciente complejidad de los modelos de PNs y del software que los implementa, requiere que los cambios o las mejoras sean sopesados cuidadosamente contra el impacto que su introducción tendrá; también deben llevarse a cabo de manera sistemática para asegurar un desarrollo exitoso. Dos elementos son clave para proveer estos requisitos: la separación de la definición de los PNs de su implementación, para minimizar el impacto de los cambios de uno en otro, y un proceso para introducir los cambios o mejoras en los PNs y/o en el software que los implementa. La Gestión de Procesos de Negocio (Business Process Management, BPM) proporciona los medios para guiar y apoyar el modelado, implementación, despliegue, ejecución y evaluación de PNs en una organización, basado en el ciclo de vida de PNs. La realización de PNs con servicios proporciona la base para la separación de su definición de las tecnologías para implementarlos, y ayuda a proporcionar una mejor respuesta a los cambios en cualquiera de las capas definidas -definición e implementación de procesos de negocio- con un impacto mínimo sobre la otra. El modelado de PNs y servicios es un aspecto clave para apoyar esta visión, ayudando a proveer trazabilidad entre los elementos de un área a la otra, por lo tanto facilitando el análisis del impacto de los cambios, entre otras cosas. Los modelos han demostrado jugar un papel importante en el proceso de desarrollo de software, uno de sus usos principales en el contexto de la realización de PNs con servicios es el de diseñar servicios a un nivel más abstracto que con tecnologías específicas, promoviendo la reutilización separando la lógica de los servicios de su implementacion. MINERVA: Model drIveN & sErvice oRiented framework for the continuous business process improVement & relAted tools es el marco que se ha definido en este trabajo de tesis, que toma en cuenta todos los aspectos mencionados, en el cual los paradigmas de Computación Orientada a Servicios (Service Oriented Computing, SOC) y Desarrollo Dirigido por Modelos (Model Driven Development, MDD) se aplican a los PNs con foco en su mejora continua, extendiendo un ciclo de vida PN existente con actividades y elementos explícitos para la medición de la ejecución y mejora de PNs. El marco se compone de tres dimensiones: i) conceptual, que define los conceptos que se manejan en todo el marco. ii) metodológica, que define una metodología para el desarrollo orientado a servicios desde PNs, con generación automática de modelos de servicio en SoaML desde modelos en BPMN2, junto con un proceso de mejora continua basado en la medición de la ejecución de las ocurrencias de los PNs en la organización para llevar a cabo el esfuerzo de mejora. iii) soporte de herramientas para la propuesta completa basado en la integracion de varias herramientas existentes, junto con otras nuevas que hemos desarrollado. Las propuestas de MINERVA han sido validadas por medio de un experimento y dos casos de estudio realizados en el marco de proyectos reales en dos organizaciones, de los cuales, como resultado principal de las aplicaciones realizadas, se puede concluir que MINERVA puede ser una guía útil y clave para la mejora continua de PNs realizados por servicios y para el desarrollo de sistemas orientados a servicios desde PNs, con generación automática de modelos de servicio a partir de modelos de PN

Applying Process-Oriented Data Science to Dentistry

Background: Healthcare services now often follow evidence-based principles, so technologies such as process and data mining will help inform their drive towards optimal service delivery. Process mining (PM) can help the monitoring and reporting of this service delivery, measure compliance with guidelines, and assess effectiveness. In this research, PM extracts information about clinical activity recorded in dental electronic health records (EHRs) converts this into process-models providing stakeholders with unique insights to the dental treatment process. This thesis addresses a gap in prior research by demonstrating how process analytics can enhance our understanding of these processes and the effects of changes in strategy and policy over time. It also emphasises the importance of a rigorous and documented methodological approach often missing from the published literature. Aim: Apply the emerging technology of PM to an oral health dataset, illustrating the value of the data in the dental repository, and demonstrating how it can be presented in a useful and actionable manner to address public health questions. A subsidiary aim is to present the methodology used in this research in a way that provides useful guidance to future applications of dental PM. Objectives: Review dental and healthcare PM literature establishing state-of-the-art. Evaluate existing PM methods and their applicability to this research’s dataset. Extend existing PM methods achieving the aims of this research. Apply PM methods to the research dataset addressing public health questions. Document and present this research’s methodology. Apply data-mining, PM, and data-visualisation to provide insights into the variable pathways leading to different outcomes. Identify the data needed for PM of a dental EHR. Identify challenges to PM of dental EHR data. Methods: Extend existing PM methods to facilitate PM research in public health by detailing how data extracts from a dental EHR can be effectively managed, prepared, and used for PM. Use existing dental EHR and PM standards to generate a data reference model for effective PM. Develop a data-quality management framework. Results: Comparing the outputs of PM to established care-pathways showed that the dataset facilitated generation of high-level pathways but was less suitable for detailed guidelines. Used PM to identify the care pathway preceding a dental extraction under general anaesthetic and provided unique insights into this and the effects of policy decisions around school dental screenings. Conclusions: Research showed that PM and data-mining techniques can be applied to dental EHR data leading to fresh insights about dental treatment processes. This emerging technology along with established data mining techniques, should provide valuable insights to policy makers such as principal and chief dental officers to inform care pathways and policy decisions

Improving IT service management using an ontology-based and model-driven approach

Texto en inglés y resumen en inglés y españolLa adopción de marcos de trabajo de mejores prácticas que permiten la integración de las Tecnologías de la Información (TI) con el negocio, ayuda a las organizaciones a crear y compartir procesos de gestión de servicios de TI. Sin embargo, las guías y modelos publicados suelen especificarse en lenguaje natural o con representaciones gráficas que carecen de la semántica computacional necesaria para poder automatizar su validación, simulación e incluso su ejecución. En esta tesis se presenta Onto-ITIL, una propuesta basada en ontologías y en el enfoque de desarrollo de software dirigido por modelos que captura las mejores prácticas ofrecidas por ITIL® (del inglés Information Technology Infrastructure Library), y destinada a facilitar la prestación de servicios de TI. El objetivo de Onto-ITIL es ayudar a los expertos del dominio a modelar e implementar procesos de gestión de servicios de TI evitando ambigüedades semánticas y contradicciones. La formalización de los procesos de gestión de servicios de TI en términos de ITIL constituye un primer paso para cubrir la brecha que se da entre el negocio y las TI. Para definir las ontologías se ha utilizado OWL (del inglés Web Ontology Language). Adicionalmente, se ha definido un conjunto de reglas basadas en SWRL (del inglés Semantic Web Rule Language) que permiten enriquecer la ontología con una serie de restricciones semánticas y de reglas de inferencia de conocimiento. Por último, la definición de un conjunto de consultas basadas en SQWRL (del inglés Query-Enhanced Web Rule Language) permite recuperar conocimiento obtenido con OWL e inferido a través de las reglas SWRL. Además de formalizar los procesos de gestión de servicios de TI en base a las buenas prácticas consideradas por ITIL, Onto-ITIL también permite compartir, reutilizar e intercambiar las especificaciones de dichos procesos a través de mecanismos automatizados que proporcionan ciertos marcos de trabajo de comercio electrónico, como por ejemplo, ebXML. Mediante la adopción del enfoque MDE (del inglés Model-driven Engineering), se ha utilizado un DSL (del inglés Domain Specific Language) basado en la ontología Onto-ITIL que sirve para implementar sistemas de información basados en flujos de trabajo que dan soporte a los Sistemas de Gestión de Servicios de TI (SGSTI). Los modelos que se obtienen a partir de este lenguaje de modelado se pueden considerar modelos de alto nivel que han sido enriquecidos con conocimiento ontológico, y que están definidos exclusivamente en términos de lógica de negocio, es decir, que no presentan ningún aspecto arquitectónico o de plataforma de implementación. Con lo cual, de acuerdo con la arquitectura en cuatro capas propuesta por el OMG (del inglés Object Management Group), estos modelos se encontrarían a nivel CIM (del inglés Computation Independent Model). En resumen, la propuesta presentada en esta tesis permite: (i) formalizar el conocimiento asociado a los sistemas de gestión de servicios de TI en base a ontologías que recogen las buenas prácticas consideradas por ITIL; (ii) modelar la semántica de las actividades que definen los procesos de gestión de servicios de TI en forma de flujos de trabajo; (iii) generar de manera automática modelos de requisitos de alto nivel para implementar sistemas de información que se necesitan para dar soporte a dichos procesos; y (iv) a partir de los modelos anteriores, obtener modelos de más bajo nivel (llegando incluso al código de las aplicaciones) a través de transformaciones automáticas de modelos. La investigación llevada a cabo en esta tesis se ha validado mediante de la implementación de un caso de estudio real proporcionado por una compañía española que ofrece servicios de TI

Improving IT service management using an ontology-based and model-driven approach

Texto en inglés y resumen en inglés y españolLa adopción de marcos de trabajo de mejores prácticas que permiten la integración de las Tecnologías de la Información (TI) con el negocio, ayuda a las organizaciones a crear y compartir procesos de gestión de servicios de TI. Sin embargo, las guías y modelos publicados suelen especificarse en lenguaje natural o con representaciones gráficas que carecen de la semántica computacional necesaria para poder automatizar su validación, simulación e incluso su ejecución. En esta tesis se presenta Onto-ITIL, una propuesta basada en ontologías y en el enfoque de desarrollo de software dirigido por modelos que captura las mejores prácticas ofrecidas por ITIL® (del inglés Information Technology Infrastructure Library), y destinada a facilitar la prestación de servicios de TI. El objetivo de Onto-ITIL es ayudar a los expertos del dominio a modelar e implementar procesos de gestión de servicios de TI evitando ambigüedades semánticas y contradicciones. La formalización de los procesos de gestión de servicios de TI en términos de ITIL constituye un primer paso para cubrir la brecha que se da entre el negocio y las TI. Para definir las ontologías se ha utilizado OWL (del inglés Web Ontology Language). Adicionalmente, se ha definido un conjunto de reglas basadas en SWRL (del inglés Semantic Web Rule Language) que permiten enriquecer la ontología con una serie de restricciones semánticas y de reglas de inferencia de conocimiento. Por último, la definición de un conjunto de consultas basadas en SQWRL (del inglés Query-Enhanced Web Rule Language) permite recuperar conocimiento obtenido con OWL e inferido a través de las reglas SWRL. Además de formalizar los procesos de gestión de servicios de TI en base a las buenas prácticas consideradas por ITIL, Onto-ITIL también permite compartir, reutilizar e intercambiar las especificaciones de dichos procesos a través de mecanismos automatizados que proporcionan ciertos marcos de trabajo de comercio electrónico, como por ejemplo, ebXML. Mediante la adopción del enfoque MDE (del inglés Model-driven Engineering), se ha utilizado un DSL (del inglés Domain Specific Language) basado en la ontología Onto-ITIL que sirve para implementar sistemas de información basados en flujos de trabajo que dan soporte a los Sistemas de Gestión de Servicios de TI (SGSTI). Los modelos que se obtienen a partir de este lenguaje de modelado se pueden considerar modelos de alto nivel que han sido enriquecidos con conocimiento ontológico, y que están definidos exclusivamente en términos de lógica de negocio, es decir, que no presentan ningún aspecto arquitectónico o de plataforma de implementación. Con lo cual, de acuerdo con la arquitectura en cuatro capas propuesta por el OMG (del inglés Object Management Group), estos modelos se encontrarían a nivel CIM (del inglés Computation Independent Model). En resumen, la propuesta presentada en esta tesis permite: (i) formalizar el conocimiento asociado a los sistemas de gestión de servicios de TI en base a ontologías que recogen las buenas prácticas consideradas por ITIL; (ii) modelar la semántica de las actividades que definen los procesos de gestión de servicios de TI en forma de flujos de trabajo; (iii) generar de manera automática modelos de requisitos de alto nivel para implementar sistemas de información que se necesitan para dar soporte a dichos procesos; y (iv) a partir de los modelos anteriores, obtener modelos de más bajo nivel (llegando incluso al código de las aplicaciones) a través de transformaciones automáticas de modelos. La investigación llevada a cabo en esta tesis se ha validado mediante de la implementación de un caso de estudio real proporcionado por una compañía española que ofrece servicios de TI

AVENTIS - An architecture for event data analysis

Time-stamped event data is being generated at an exponential rate from various sources (sensor networks, e-markets etc.), which are stored in event logs and made available to researchers. Despite the data deluge and evolution of a plethora of tools and technologies, science behind exploratory analysis and knowledge discovery lags. There are several reasons behind this. In conducting event data analysis, researchers typically detect a pattern or trend in the data through computation of time-series measures and apply the computed measures to several mathematical models to glean information from data. This is a complex and time-consuming process covering a range of activities from data capture (from a broad array of data sources) to interpretation and dissemination of experimental results forming a pipeline of activities. Further, data-analysis is conducted by domain-users, who are typically non-IT experts but data processing tools and applications are largely developed by application developers. End-users not only lack the critical skills to build a structured analysis pipeline, but are also perplexed by the number of different ways available to derive the necessary information. Consequently, this thesis proposes AVENTIS (Architecture for eVENT Data analysIS), a novel framework to guide the design of analytic solutions to facilitate time-series analysis of event data and is tailored to the needs of domain users. The framework comprises three components; a knowledge base, a model-driven analytic methodology and an accompanying software architecture that provides the necessary technical and operational requirements. Specifically, the research contribution lies in the ability of the framework to enable expressing analysis requirements at a level of abstraction consistent with the domain users and readily make available the information sought without the users having to build the analysis process themselves. Secondly, the framework also facilitates an abstract design space for the domain experts to enable them to build conceptual models of their experiment as a sequence of structured tasks in a technology neutral manner and transparently translate these abstract process models to executable implementations. To evaluate the AVENTIS framework, a prototype based on AVENTIS is implemented and tested with case studies taken from the financial research domain