Beyond Control-Flow: Extending Business Process Configuration to Roles and Objects

A configurable process model is an integrated representation of multiple variants of a business process. It is designed to be individualized to meet a particular set of requirements. As such, configurable process models promote systematic reuse of proven or common practices. Existing notations for configurable process modeling focus on capturing tasks and control-flow dependencies, neglecting equally important aspects of business processes such as data flow, material flow and resource management. This paper fills this gap by proposing an integrated meta-model for configurable processes with advanced features for capturing resources involved in the performance of tasks (through task-role associations) as well as flow of data and physical artifacts (through task-object associations). Although embodied as an extension of a popular process modeling notation, namely EPC, the meta-model is defined in an abstract and formal manner to make it applicable to other notations

A DSDEVS-Based Model for Verifying Structural Constraints in Dynamic Business Processes

This paper presents a DSDEVS-based model “Dynamic Structure Discrete Event System specification” for modeling and simulating business processes with dynamic structure regarding to different contexts. Consequently, this model, formally, improves the reuse of configurable business processes. Thus, the proposed model allows the analysts to personalize their configurable business processes in a sound manner by verifying a set of structure properties, such as, the lack of synchronization and the deadlock by means of simulation. The implementation was done in DEVS-Suite simulator, which is based on DEVSJAVA models

Modeling Business Process Variability

This master thesis presents research findings on business process variability modeling. Its main goal is to analyze inherent problems of business process variability and solve them simply, innovatively and effectively. To achieve this goal, process variability is defined by analyzing scientific literature, its main problems identified and is illustrated using a healthcare running example: process variability is classified into process variability within the domain space and over time. These two forms of process variability respectively lead to process variability modeling and process model evolution problems. After defining the main problems inherent to process variability, the focus of this research project is defined: solving process variability modeling problems. First current business process modeling languages are evaluated to assess the effectiveness of their respective modeling concepts when modeling process variability, using a newly created set of evaluation criteria and the healthcare running example. The following business process modeling languages are evaluated: Event driven process chains (EPC), the Business Process Modeling Notation (BPMN) and Configurable EPC (C-EPC). Business process variability modeling and Software product line engineering have similar problems. Therefore the variability modeling concepts developed by software product line engineering are analyzed. Feature diagrams and software configuration management are the main variability management concepts provided by software product line engineering. To apply these variability management concepts to model process variability meant combining them with existing business modeling languages. Riebisch feature diagrams are combined with C-EPC to form Feature-EPC. Applying software configuration management, meant merging Change Oriented Versioning with basic EPC to create COV-EPC, and merging the Proteus Configuration Language with basic EPC to design PCL-EPC. Finally these newly created business process modeling languages are also evaluated using the newly designed evaluation criteria and the healthcare running example. EPC or BPMN are not suited to model business process variability within the domain space. C-EPC provide explicit means to model business process variability, however the process models tend to get big very fast. Furthermore the syntax, the contextual constraints and the semantics of the configuration requirements and guidelines used to configure the C-EPC process models are unclear. Feature-EPC improve C-EPC with domain modeling capability and clearly defined configuration rules: their syntax, contextual constraints and semantics have been clearly defined using a context free grammar in Backus-Naur form. Furthermore, consistent combinations of features and configuration rules are ensured using respectively constraints and a conflict resolution algorithm. However, Feature-EPC and C-EPC suffer from the same weakness: large configurable process models. In COV-EPC and PCL-EPC the problem of large configurable process models is solved. COV-EPC ensures consistent combinations of options and configuration rules using respectively validities and a conflict resolution algorithm. PCL-EPC guarantees consistent combinations of process fragments by means of a PCL specification

Modeling Variability in the Performance Perspective of Business Processes

The modeling and management of business processes often leads to the definition of several variants of the same process. This variability can be reflected in different process perspectives such as control-flow, data, resources or performance. The management of process variants can be a laborious, time-consuming and error-prone task since they require a high coordination in the management of each variant and in most cases this management is done manually. For this reason, many proposals have been developed to deal with the variability of business processes. However, none of them covers in detail the variability in the performance perspective, which is concerned with the definition of performance requirements usually specified as a set of Process Performance Indicators (PPIs). This variability can be reflected in the form of repetitive and redundant PPI definitions, and can lead to errors and inconsistencies in PPI definitions. To address this problem, in this article we propose a detailed PPI variability classification and a formalization of how PPIs can be modeled together with the variability of other process perspectives. To this end, we considered variability management approaches, called by restriction and by extension, and we illustrated our proposal by integrating it with existing variability modeling languages. An evaluation conducted in two scenarios shows the feasibility and usefulness of our proposal.Ministerio de Ciencia e Innovación HORATIO (RTI2018-101204–B–C21)Ministerio de Ciencia e Innovación OPHELIA (RTI2018101204-B-C22)Junta de Andalucía APOLO (US-1264651)Junta de Andalucía EKIPMENT-PLUS (P18-FR-2895

Configurable Process Models as a Basis for Reference Modeling

Off-the-shelf packages such as SAP need to be configured to suit the requirements of an organization. Reference models support the configuration of these systems. Existing reference models use rather traditional languages. For example, the SAP reference model uses Eventdriven Process Chains (EPCs). Unfortunately, traditional languages like EPCs do not capture the configuration-aspects well. Consider for example the concept of "choice" in the control-flow perspective. Although any process modeling language, including EPCs, offers a choice construct (e.g., the XOR connector in EPCs), a single construct will not be able to capture the time dimension, scope, and impact of a decision. Some decisions are taken at run-time for a single case while other decisions are taken at build-time impacting a whole organization and all current and future cases. This position paper discusses the need for configurable process models as a basic building block for reference modeling. The focus is on the control-flow perspective. © Springer-Verlag Berlin Heidelberg 2006

A Meta Model Based Extension of BPMN 2.0 for Mobile Context Sensitive Business Processes and Applications

Smart devices like smartphones or tablets have become ubiquitous, which affected many daily work activities like maintaining contacts via a mobile CRM anywhere, anytime. Thus, business processes can now be executed independently of an employee’s location. In addition, mobile devices have the possibility to measure physical quantities through sensors, like location or acceleration. Moreover, the connection to wireless networks made it possible to query context information like customer history. These context information can be used to adapt mobile business processes and the mobile application that support them. But in order to use this advantage, mobile sensor data has to be reflected in the business process model. As current languages for process aware information systems, such as BPMN, do not support the influence of mobile context information, we propose an extension of the BPMN that will enable the modeling of mobile context sensitive business processes

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

Variability management in process families through change patterns

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Context: The increasing adoption of process-aware information systems together with the high variability in business processes has resulted in collections of process families. These families correspond to a business process model and its variants, which can comprise hundreds or thousands of different ways of realizing this process. Managing process variability in this context can be very challenging, labor-intensive, and error-prone, and new approaches for managing process families are necessary. Objective: We aim to facilitate variability management in process families, ensure process family correctness, and reduce the effort needed for such purposes. Method: We have derived a set of change patterns for process families from variability-specific language constructs identified in the literature. For validation, we have conducted a case study with a safety standard in which we have measured the number of operations needed to model and evolve the variability of the standard with and without the patterns. Results: We present 10 change patterns for managing variability in process families and show how they can be implemented. The patterns support the modeling and evolution of process families and ensure process family correctness by automatically introducing and deleting modeling elements. The case study results show that the application of the defined change patterns can reduce the number of operations when modeling a process family by 34% and when evolving it by 40%. Conclusions: The application of the change patterns can help in effectively modeling and evolving large and highly-variable process families. Their application can also considerably reduce variability management effort. (C) 2016 Elsevier B.V. All rights reserved.This work has been developed with the financial support of Spanish Ministry of Economy and Competitiveness under the project SMART-ADAPT TIN2013-42981-P. We also want to thank Barbara Weber and Manfred Reichert for their valuable input and feedback on the design and development of the set of change patterns for process families.Ayora Esteras, C.; Torres Bosch, MV.; De La Vara González, JL.; Pelechano Ferragud, V. (2016). Variability management in process families through change patterns. Information and Software Technology. 74:86-104. https://doi.org/10.1016/j.infsof.2016.01.007S861047