at the 14th Conference of the Spanish Association for Artificial Intelligence (CAEPIA 2011)

Technical Report TR-2011/1, Department of Languages and Computation. University of Almeria November 2011. Joaquín Cañadas, Grzegorz J. Nalepa, Joachim Baumeister (Editors)The seventh workshop on Knowledge Engineering and Software Engineering (KESE7) was held at the Conference of the Spanish Association for Artificial Intelligence (CAEPIA-2011) in La Laguna (Tenerife), Spain, and brought together researchers and practitioners from both fields of software engineering and artificial intelligence. The intention was to give ample space for exchanging latest research results as well as knowledge about practical experience.University of Almería, Almería, Spain. AGH University of Science and Technology, Kraków, Poland. University of Würzburg, Würzburg, Germany

Quality measures for ETL processes: from goals to implementation

Extraction transformation loading (ETL) processes play an increasingly important role for the support of modern business operations. These business processes are centred around artifacts with high variability and diverse lifecycles, which correspond to key business entities. The apparent complexity of these activities has been examined through the prism of business process management, mainly focusing on functional requirements and performance optimization. However, the quality dimension has not yet been thoroughly investigated, and there is a need for a more human-centric approach to bring them closer to business-users requirements. In this paper, we take a first step towards this direction by defining a sound model for ETL process quality characteristics and quantitative measures for each characteristic, based on existing literature. Our model shows dependencies among quality characteristics and can provide the basis for subsequent analysis using goal modeling techniques. We showcase the use of goal modeling for ETL process design through a use case, where we employ the use of a goal model that includes quantitative components (i.e., indicators) for evaluation and analysis of alternative design decisions.Peer ReviewedPostprint (author's final draft

makeSense: Simplifying the Integration of Wireless Sensor Networks into Business Processes

A wide gap exists between the state of the art in developing Wireless Sensor Network (WSN) software and current practices concerning the design, execution, and maintenance of business processes. WSN software is most often developed based on low-level OS abstractions, whereas business process development leverages high-level languages and tools. This state of affairs places WSNs at the fringe of industry. The makeSense system addresses this problem by simplifying the integration of WSNs into business processes. Developers use BPMN models extended with WSN-specific constructs to specify the application behavior across both traditional business process execution environments and the WSN itself, which is to be equipped with application-specific software. We compile these models into a high-level intermediate language—also directly usable by WSN developers—and then into OS-specific deployment-ready binaries. Key to this process is the notion of meta-abstraction, which we define to capture fundamental patterns of interaction with and within the WSN. The concrete realization of meta-abstractions is application-specific; developers tailor the system configuration by selecting concrete abstractions out of the existing codebase or by providing their own. Our evaluation of makeSense shows that i) users perceive our approach as a significant advance over the state of the art, providing evidence of the increased developer productivity when using makeSense; ii) in large-scale simulations, our prototype exhibits an acceptable system overhead and good scaling properties, demonstrating the general applicability of makeSense; and, iii) our prototype—including the complete tool-chain and underlying system support—sustains a real-world deployment where estimates by domain specialists indicate the potential for drastic reductions in the total cost of ownership compared to wired and conventional WSN-based solutions

BPMNt : a proposal for flexible process tailoring representation in BPMN /

Business Process Model and Notation (BPMN) is a de-facto standard for business process modeling, which focuses on the representation of the process behavior. However, it can also succeed in representing the behavior of software processes, since they are a type of business process. Although BPMN has been extensively used for modeling processes in different domains, its standard specification does not have any mechanism to support users in activities related to process adaptation (tailoring). Moreover, researches extending BPMN are based on complex consolidated models, which hamper the analysis and maintenance of individual variant process models and are not appropriate for application domains in which process variations are difficult to predict, such as in software development processes. Thus, our objective was to provide a BPMN-compliant extension and associated mechanisms for specifying flexible process tailoring on models produced with this language while ensuring the correctness of adapted process models and explicitly capturing change traces. We have focused our research on the domains of Software Process Engineering (SPE) and Business Process Management (BPM). At last, we evaluated the applicability of the proposal for representing realistic tailoring scenarios in both domains.BPMN (Business Process Model and Notation) é um padrão para modelagem de processos de negócio, que tem seu foco na representação do comportamento de processos. No entanto, ele pode também ser usado para representar o comportamento de processos de software, já que eles são um tipo de processo de negócio. Embora BPMN tem sido extensivamente usado para modelar processos em diferentes domínios, sua especificação padrão não possui nenhum mecanismo para apoiar usuários em atividades relacionadas à adaptação de processos. Pesquisas que estendem o padrão são baseadas em modelos complexos, que dificultam a análise e manutenção de modelos variantes, e não são apropriadas para domínios de aplicação onde variações de processo são difíceis de predizer, como em processos de desenvolvimento de software. Assim, nosso objetivo foi fornecer uma extensão para BPMN, chamada BPMNt, e mecanismos de suporte para especificar, de modo flexível, adaptações em processos modelados com esta linguagem. BPMNt deve também garantir a corretude de modelos adaptados e explicitamente capturar rastros de mudanças realizadas. Essa pesquisa teve como foco os domínios de Engenharia de Processos de Software e Gerenciamento de Processos de Negócio. Por fim, nós avaliamos a aplicabilidade da proposta para representar cenários de adaptação reais em ambos os domínios

Quality of process modeling using BPMN: a model-driven approach

Dissertação para obtenção do Grau de Doutor em Engenharia InformáticaContext: The BPMN 2.0 specification contains the rules regarding the correct usage of the language’s constructs. Practitioners have also proposed best-practices for producing better BPMN models. However, those rules are expressed in natural language, yielding sometimes ambiguous interpretation, and therefore, flaws in produced BPMN models. Objective: Ensuring the correctness of BPMN models is critical for the automation of processes. Hence, errors in the BPMN models specification should be detected and corrected at design time, since faults detected at latter stages of processes’ development can be more costly and hard to correct. So, we need to assess the quality of BPMN models in a rigorous and systematic way. Method: We follow a model-driven approach for formalization and empirical validation of BPMN well-formedness rules and BPMN measures for enhancing the quality of BPMN models. Results: The rule mining of BPMN specification, as well as recently published BPMN works, allowed the gathering of more than a hundred of BPMN well-formedness and best-practices rules. Furthermore, we derived a set of BPMN measures aiming to provide information to process modelers regarding the correctness of BPMN models. Both BPMN rules, as well as BPMN measures were empirically validated through samples of BPMN models. Limitations: This work does not cover control-flow formal properties in BPMN models, since they were extensively discussed in other process modeling research works. Conclusion: We intend to contribute for improving BPMN modeling tools, through the formalization of well-formedness rules and BPMN measures to be incorporated in those tools, in order to enhance the quality of process modeling outcomes