Dynamic variability support in context-aware workflow-based systems

Workflow-based systems are increasingly becomingmore complex and dynamic. Besides the large sets of process variants to be managed, process variants need to be context sensitive in order to accommodate new user requirements and intrinsic complexity. This paradigm shift forces us to defer decisions to run time where process variants must be customized and executed based on a recognized context. However, few efforts have been focused on dynamic variability for process families. This dissertation proposes an approach for variant-rich workflow-based systems that can comprise context data while deferring process configuration to run time. Whereas existing early process variability approaches, like Worklets, VxBPEL, or Provop handle run-time reconfiguration, ours lets us resolve variants at execution time and supports multiple binding required for dynamic environments. Finally, unlike the specialized reconfiguration solutions for some workflow-based systems, our approach allows an automated decision making, enabling different run-time resolution strategies that intermix constraint solving and feature models. We achieve these results through a simple extension to BPMN that adds primitives for process variability constructs. We show that this is enough to eficiently model process variability while preserving separation of concerns. We implemented our approach in the LateVa framework and evaluated it using both synthetic and realworld scenarios. LateVa achieves a reasonable performance over runtime resolution, which means that can facilitate practical adoption in context-aware and variant-rich work ow-based systems

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

Dynamic adaptation of service compositions with variability models

Web services run in complex contexts where arising events may compromise the quality of the whole system. Thus, it is desirable to count on autonomic mechanisms to guide the self-adaptation of service compositions according to changes in the computing infrastructure. One way to achieve this goal is by implementing variability constructs at the language level. However, this approach may become tedious, difficult to manage, and error-prone. In this paper, we propose a solution based on a semantically rich variability model to support the dynamic adaptation of service compositions. When a problematic event arises in the context, this model is leveraged for decision-making. The activation and deactivation of features in the variability model result in changes in a composition model that abstracts the underlying service composition. These changes are reflected into the service composition by adding or removing fragments of Business Process Execution Language (WS-BPEL) code, which can be deployed at runtime. In order to reach optimum adaptations, the variability model and its possible configurations are verified at design time using Constraint Programming. An evaluation demonstrates several benefits of our approach, both at design time and at runtime.This work has been developed with the support of MICINN under the project everyWare TIN2010-18011 and co-financed with ERDF.Alférez Salinas, GH.; Pelechano Ferragud, V.; Mazo, R.; Salinesi, C.; Díaz, D. (2014). Dynamic adaptation of service compositions with variability models. Journal of Systems and Software. 91:24-47. https://doi.org/10.1016/j.jss.2013.06.034S24479

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

A Generic method for assembling software product line components

Software product lines (SPL) facilitate the industrialization of software development. The main goal is to create a set of reusable software components for the rapid production of a software systems family. Many authors propose different approaches to implement and assemble the reusable components of an SPL. However, the construction and assembly of these components continue to be a complex and time-consuming process. This thesis analyzes the advantages and disadvantages of the current approaches to implement and assemble the reusable components of an SPL. Taking advantage of these elements and with the goal of developing a generic method (which can be applied to several software components developed in different software languages), we develop Fragment-oriented programming (FragOP), a framework to design, implement and reuse SPL domain components. FragOP is based on: (i) domain components, (ii) domain files, (iii) fragmentation points, (iv) fragments, (v) customization points, and (vi) customization files. FragOP was implemented in an open-source tool called VariaMos, and we also carried out three evaluations: (i) we created a clothing stores SPL, derived five different products, and discussed the results. (ii) We developed a discussion about the comparison between FragOP and other approaches. And (iii) we designed and executed a usability test of VariaMos to support the FragOP approach. The results show preliminary evidence that the use of FragOP reduces the manual intervention when assembling SPL domain components and it can be used as a generic method for assembling assets and SPL components developed in different software languages.Las líneas de productos de software (LPS) promueven la industrialización del desarrollo de software mediante la definición y ensamblaje de componentes reutilizables de software. Actualmente existen diferentes propuestas para implementar y ensamblar estos componentes. Sin embargo, su construcción y ensamblaje continúa siendo un proceso complejo y que requiere mucho tiempo. Esta tesis analiza las ventajas y desventajas de las diferentes estrategias actuales para implementación y ensamblaje de componentes de LPS. Con base en esto y con el objetivo de desarrollar un método genérico (el cual se pueda aplicar a múltiples componentes de software desarrollados en diferentes lenguajes), esta tesis desarrolla la programación orientada a fragmentos (FragOP), la cual define un marco de trabajo para diseñar, implementar y reutilizar componentes de dominio de LPS. FragOP se basa en: (i) componentes de dominio, (ii) archivos de dominio, (iii) puntos de fragmentación, (iv) fragmentos, (v) puntos de personalización, y (vi) archivos de personalización. Además, se realizó una implementación de FragOP en una herramienta llamada VariaMos, y se llevaron a cabo tres evaluaciones: (i) se creó una LPS de tiendas de ropa, se derivaron cinco productos y se discutieron los resultados. (ii) Se realizó una discusión acerca de la comparación de FragOP y otras propuestas actuales. Y (iii) se diseñó una prueba de usabilidad acerca del soporte de VariaMos para FragOP. Los resultados muestran evidencia preliminar de que el uso de FragOP reduce la intervención manual cuando se ensamblan componentes, y que FragOP puede usarse como un método genérico para el ensamblaje de componentes.Doctorad

Achieving autonomic Web service compositions with models at runtime

[EN] Several exceptional situations may arise in the complex, heterogeneous, and changing contexts where Web service operations run. For instance, a Web service operation may have greatly increased its execution time or may have become unavailable. The contribution of this article is to provide a tool-supported framework to guide autonomic adjustments of context-aware service compositions using models at runtime. During execution, when problematic events arise in the context, models are used by an autonomic architecture to guide changes of the service composition. Under the closed-world assumption, the possible context events are fully known at design time. Nevertheless, it is difficult to foresee all the possible situations arising in uncertain contexts where service compositions run. Therefore, the proposed framework also covers the dynamic evolution of service compositions to deal with unexpected events in the open world. An evaluation demonstrates that our framework is efficient during dynamic adjustments.Alférez-Salinas, GH.; Pelechano Ferragud, V. (2017). Achieving autonomic Web service compositions with models at runtime. Computers & Electrical Engineering. 63:332-352. doi:10.1016/j.compeleceng.2017.08.004S3323526

Linha de produtos de software dinâmica direcionada por qualidade : o caso de redes de monitoração do corpo humano

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2012.Na atualidade, os indivíduos passam a ter uma posição mais ativa no processo de investigação de doenças querendo acompanhar o seu estado de saúde continuamente. Por ser é inviável manter um profissional de saúde para cada indivíduo, mais apoio da tecnologia tem sido requerido a fim de auxiliar esse processo de monitoração. Diante deste quadro, mais soluções automatizadas estão sendo propostas, em particular, Redes de Sensores do Corpo Humano (RSCH), no qual um indivíduo monitora suas atividades diárias e sinais vitais e o sistema o auxilia na prevenção e detecção de situações de emergência. Este trabalho explora como a metodologia de Linha de Produto de Software Dinâmica (LPSD) no contexto de RSCH gerencia e balanceia requisitos conflitantes, tais como disponibilidade e confiabilidade, de tal forma que quando o indivíduo estiver em uma situação normal de saúde, o sistema possa desativar alguns sensores ou funcionalidades visando economia de bateria e processamento; e por outro lado, quando o indivíduo desmaiar ou alterar seus batimentos cardíacos, o oposto deva acontecer com os sensores afim de se prover o melhor serviço para o indivíduo em uma situação de alto risco de saúde. Uma LPSD para RSCH se reconfigura baseando-se em mudanças de contexto, no caso, mudança na situação de saúde do indivíduo monitorado, afim de atingir um novo objetivo de qualidade para esta nova situação de risco. Neste trabalho, a situação de um indivíduo é especificada como um contrato de qualidade, provido por um especialista no domínio (médico). O contrato é modelado como uma máquina de estados, onde as transições entre estados são causadas por eventos de saúde (queda, desmaio, alteração de pressão) e os estados definem objetivos de qualidade. A verificação de não conformidade com o objetivo de qualidade motiva a reconfiguração do sistema. A confiabilidade de uma determinada configuração é medida como uma única fórmula, parametrizada com a presença e ausência das features da LPSD e das qualidades associadas a elas. Além de confiabilidade, exploram-se também parâmetros de qualidade tais como tempo de vida estimado para o sistema, taxa de amostragem, qualidade e quantidade de informação das configurações. As estratégias de cálculo de qualidade Simple MultiAttribute Rating Technique (SMART) e orientação a objetivos (GOAL) são comparadas no domínio de RSCH. Avaliou-se a abordagem proposta via simulações com dados reais de monitoração e obteve-se resultado favorável à utilização da metodologia proposta no contexto. _______________________________________________________________________________________________________________________________ ABSTRACTNowadays, individuals have a more active stance in the investigation of diseases in the sense that they want to monitor their health status continuously. Because it is not sustainable to have dedicated health professional for each individual, more technology support has been applied to assist this monitoring process. In this context, automatic solutions are being proposed, in particular Body Sensor Network (BSN), in which an individual monitors his vital signs and the system aids him in the prevention and detection of emergency situations. BSN must manage and balance conflicting requirements, such as availability and reliability, in a way that if the patient is in a normal or low health risk situation, the system can turn off some sensors or disable features to save power and processing. On the other hand, when the individual faints or changes its heartbeats dangerously, the opposite should happen with the sensors and features in order to provide the best service for this high risk situation. We explore how Dynamic Software Product Line (DSPL) achieves this goal. A DSPL reconfigures itself based on some context changes e.g., the persons' medical situation, to meet a new quality goal for that new situation, as specified by a reliability contract provided by the domain expert (a medical doctor). This contract is modeled as a state machine, whose transitions are medical events (e.g., fall, stroke) and states are target reliability goals, prompting a reconfiguration to meet it. The reliability of any given configuration is measured by a single formula, parametrizing over the features of the DSPL and related quality information. Besides reliability, we also explore other quality parameters such as lifetime, sensor sample rate, quality and amount of information. Strategies for calculating quality such as Simple MultiAttribute Rating Technique (SMART) and goal-oriented are compared in the BSN domain. We evaluated the proposed approach via simulations with real monitoring data and obtained favorable results with the use of the proposed methodology in the BSN context

A systematic literature review on the semi-automatic configuration of extended product lines

Product line engineering has become essential in mass customisation given its ability to reduce production costs and time to market, and to improve product quality and customer satisfaction. In product line literature, mass customisation is known as product configuration. Currently, there are multiple heterogeneous contributions in the product line configuration domain. However, a secondary study that shows an overview of the progress, trends, and gaps faced by researchers in this domain is still missing. In this context, we provide a comprehensive systematic literature review to discover which approaches exist to support the configuration process of extended product lines and how these approaches perform in practice. Extend product lines consider non-functional properties in the product line modelling. We compare and classify a total of 66 primary studies from 2000 to 2016. Mainly, we give an in-depth view of techniques used by each work, how these techniques are evaluated and their main shortcomings. As main results, our review identified (i) the need to improve the quality of the evaluation of existing approaches, (ii) a lack of hybrid solutions to support multiple configuration constraints, and (iii) a need to improve scalability and performance conditions