Procesos de Negocio

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Artículos en la categoría Procesos de Negocio publicados en las Actas de las XV Jornadas de Ciencia e Ingeniería de Servicios (JCIS 2019).
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  • Resumen
    Ensuring the Semantic Correctness of a BAUML Artifact-centric BPM
    Estañol, Montserrat; Sancho, Maria-Ribera; Teniente, Ernest. Actas de las XV Jornadas de Ciencia e Ingeniería de Servicios (JCIS 2019), 2019-09-02.
    Using models to represent business processes provides several advantages, such as being able to check the correctness of the processes before their implementation. In contrast to traditional process modeling approaches, the artifact-centric approach treats data as a key element of the process, also considering the tasks or activities that are performed in it. This paper presents a way to verify and validate the semantic correctness of an artifact-centric business process model defined using a combination of UML and OCL models - a BAUML model. To do this, we provide a method to translate all BAUML components into a set of logic formulas. The result of this translation ensures that the only changes allowed are those specified in the model, and that those changes are taking place according the order established by the model. Having obtained this logic representation, these models can be validated by any existing reasoning method able to deal with negation of derived predicates. Moreover, we show how to automatically generate the relevant tests to validate the models and we prove the feasibility of our approach.
  • Artículo
    Pattern-based Simplification of Process Models
    Chapela-Campa, David; Mucientes, Manuel; Lama Penin, Manuel. Actas de las XV Jornadas de Ciencia e Ingeniería de Servicios (JCIS 2019), 2019-09-02.
    Several simplification techniques have been proposed to deal with the understanding of complex process models, from the structural simplification of the model to the simplification of the log to discover simpler process models. But obtaining a comprehensible model explaining the behaviour of unstructured large processes is still an open challenge. In this paper, we present a novel algorithm to simplify process models by abstracting the infrequent behaviour in the logs.