Automatiser le support de la variabilité dans les modèles de processus configurables

Today's fast changing environment imposes new challenges for effective management of business processes. In such a highly dynamic environment, the business process design becomes time-consuming, error-prone, and costly. Therefore, seeking reuse and adaptability is a pressing need for a successful business process design. Configurable reference models recently introduced were a step toward enabling a process design by reuse while providing flexibility. A configurable process model is a generic model that integrates multiple process variants of a same business process in a given domain through variation points. These variation points are referred to as configurable elements and allow for multiple design options in the process model. A configurable process model needs to be configured according to a specific requirement by selecting one design option for each configurable element.Recent research activities on configurable process models have led to the specification of configurable process modeling notations as for example configurable Event-Driven Process Chain (C-EPC) that extends the EPC notation with configurable elements. Since then, the issue of building and configuring configurable process models has been investigated. On the one hand, as configurable process models tend to be very complex with a large number of configurable elements, many automated approaches have been proposed to assist their design. However, existing approaches propose to recommend entire configurable process models which are difficult to reuse, cost much computation time and may confuse the process designer. On the other hand, the research results on configurable process model design highlight the need for means of support to configure the process. Therefore, many approaches proposed to build a configuration support system for assisting end users selecting desirable configuration choices according to their requirements. However, these systems are currently manually created by domain experts which is undoubtedly a time-consuming and error-prone task.In this thesis, we aim at automating the support of the variability in configurable process models. Our objective is twofold: (i) assisting the configurable process design in a fin-grained way using configurable process fragments that are close to the designers interest and (ii) automating the creation of configuration support systems in order to release the process analysts from the burden of manually building them. In order to achieve the first objective, we propose to learn from the experience gained through past process modeling in order to assist the process designers with configurable process fragments. The proposed fragments inspire the process designer to complete the design of the ongoing process. To achieve the second objective, we realize that previously designed and configured process models contain implicit and useful knowledge for process configuration. Therefore, we propose to benefit from the experience gained through past process modeling and configuration in order to assist process analysts building their configuration support systems. Such systems assist end users interactively configuring the process by recommending suitable configuration decisions.L'évolution rapide dans les environnements métier d'aujourd'hui impose de nouveaux défis pour la gestion efficace et rentable des processus métiers. Dans un tel environnement très dynamique, la conception des processus métiers devient une tâche fastidieuse, source d'erreurs et coûteuse. Par conséquent, l'adoption d'une approche permettant la réutilisation et l'adaptabilité devient un besoin urgent pour une conception de processus prospère. Les modèles de processus configurables récemment introduits représentent l'une des solutions recherchées permettant une conception de processus par la réutilisation, tout en offrant la flexibilité. Un modèle de processus configurable est un modèle générique qui intègre de multiples variantes de procédés d'un même processus métier à travers des points de variation. Ces points de variation sont appelés éléments configurables et permettent de multiples options de conception dans le modèle de processus. Un modèle de processus configurable doit être configuré selon une exigence spécifique en sélectionnant une option de conception pour chaque élément configurable.Les activités de recherche récentes sur les modèles de processus configurables ont conduit à la spécification des langages de modélisation de processus configurables comme par exemple configurable Event-Driven Process Chain (C-EPC) qui étend la notation de l'EPC avec des éléments configurables. Depuis lors, la question de la conception et de la configuration des modèles de processus configurables a été étudiée. D'une part, puisque les modèles de processus configurables ont tendance à être très complexe avec un grand nombre d'éléments configurables, de nombreuses approches automatisées ont été proposées afin d'assister leur conception. Cependant, les approches existantes proposent de recommander des modèles de processus configurables entiers qui sont difficiles à réutiliser, nécessitent un temps complexe de calcul et peuvent confondre le concepteur du processus. D'autre part, les résultats de la recherche sur la conception des modèles de processus configurables ont mis en évidence la nécessité des moyens de soutien pour configurer le processus. Par conséquent, de nombreuses approches ont proposé de construire un système de support de configuration pour aider les utilisateurs finaux à sélectionner les choix de configuration souhaitables en fonction de leurs exigences. Cependant, ces systèmes sont actuellement créés manuellement par des experts du domaine qui est sans aucun doute une tâche fastidieuse et source d'erreurs .Dans cette thèse, nous visons à automatiser le soutien de la variabilité dans les modèles de processus configurables. Notre objectif est double: (i) assister la conception des processus configurables d'une manière à ne pas confondre les concepteurs par des recommandations complexes et (i) assister la création des systèmes de soutien de configuration afin de libérer les analystes de processus de la charge de les construire manuellement. Pour atteindre le premier objectif, nous proposons d'apprendre de l'expérience acquise grâce à la modélisation des processus passés afin d'aider les concepteurs de processus avec des fragments de processus configurables. Les fragments proposés inspirent le concepteur du processus pour compléter la conception du processus en cours. Pour atteindre le deuxième objectif, nous nous rendons compte que les modèles de processus préalablement conçus et configurés contiennent des connaissances implicites et utiles pour la configuration de processus. Par conséquent, nous proposons de bénéficier de l'expérience acquise grâce à la modélisation et à la configuration passées des processus afin d'aider les analystes de processus dans la construction de leurs systèmes de support de configuration

Modelling and Managing Variability in Business Process Models

Business Process (BP) models capture the coordination of a set of activities whose execution realizes specific business goals within a company. However, the construction of such models entails a big challenge for modellers and strongly depends on the nature of the domain being modelled. Moreover, when this nature involves handling many process alternatives, the use of variability modelling mechanisms becomes essential to succeed in the BP modelling task. Even though BP modelling variability has already been addressed by researches from the BPM community, it still remains as a challenge that is requested as hot topic in the most relevant conferences related to the BP area (i.e. the international conference on Business Process Modeling (BPM), CoopIS or BPDSM). This demand appears since the solutions provided in the literature do not deal with variability in a broad sense (considering all types of variability that we can find in a BP model), and in a scalable manner. In this context, this work provides a modelling approach that brings variability concepts as first order aspects of the modelling process. Concretely, the approach isolates the variability factors that affect a BP and allows managing independently their impact over the whole model. For such purpose, we rely on the techniques proposed in the field of the Software Product Lines to deal with variability issues. These techniques allows enhancing variability expressiveness as well as promoting model maintenance, legibility, understanding and reuse regarding variability. Finally, a running example is described and developed to illustrate the proposal and its applicability.Ayora Esteras, C. (2011). Modelling and Managing Variability in Business Process Models. http://hdl.handle.net/10251/15495Archivo delegad

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

Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

The Signal Data Explorer: A high performance Grid based signal search tool for use in distributed diagnostic applications

We describe a high performance Grid based signal search tool for distributed diagnostic applications developed in conjunction with Rolls-Royce plc for civil aero engine condition monitoring applications. With the introduction of advanced monitoring technology into engineering systems, healthcare, etc., the associated diagnostic processes are increasingly required to handle and consider vast amounts of data. An exemplar of such a diagnosis process was developed during the DAME project, which built a proof of concept demonstrator to assist in the enhanced diagnosis and prognosis of aero-engine conditions. In particular it has shown the utility of an interactive viewing and high performance distributed search tool (the Signal Data Explorer) in the aero-engine diagnostic process. The viewing and search techniques are equally applicable to other domains. The Signal Data Explorer and search services have been demonstrated on the Worldwide Universities Network to search distributed databases of electrocardiograph data

A planning approach to the automated synthesis of template-based process models

The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment

Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies

In today’s dynamic business world, the success of a company increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Companies have therefore identified process agility as a competitive advantage to address business trends like increasing product and service variability or faster time to market, and to ensure business IT alignment. Along this trend, a new generation of information systems has emerged—so-called process-aware information systems (PAIS), like workflow management systems, case handling tools, and service orchestration engines. With this book, Reichert and Weber address these flexibility needs and provide an overview of PAIS with a strong focus on methods and technologies fostering flexibility for all phases of the process lifecycle (i.e., modeling, configuration, execution and evolution). Their presentation is divided into six parts. Part I starts with an introduction of fundamental PAIS concepts and establishes the context of process flexibility in the light of practical scenarios. Part II focuses on flexibility support for pre-specified processes, the currently predominant paradigm in the field of business process management (BPM). Part III details flexibility support for loosely specified processes, which only partially specify the process model at build-time, while decisions regarding the exact specification of certain model parts are deferred to the run-time. Part IV deals with user- and data-driven processes, which aim at a tight integration of processes and data, and hence enable an increased flexibility compared to traditional PAIS. Part V introduces existing technologies and systems for the realization of a flexible PAIS. Finally, Part VI summarizes the main ideas of this book and gives an outlook on advanced flexibility issues. The attached pdf file gives a preview on Chapter 3 of the book which explains the book's overall structure

BPFlexTemplate: A Business Process template generation tool based on similarity and flexibility

In large organizations with multiple organizational units, process variants emerge due to many aspects, including local management policies, resources or socio-technical limitations. Organizations then struggle to improve a business process which has no longer a single process model to redesign, implement and adjust. In this paper, we propose an approach to tackle these two challenges: decrease the proliferation of process variants in these organizations, and foresee, at the same time, the need of having flexible business processes that allow for a certain degree of adjustment. To validate our approach, we first conducted case studies where we collected six real-world business process variants from two organizational units of the same healthcare organization. We then proposed an algorithm to derive a template process model from all the variants, which includes common and flexible process elements. We implemented our approach in a software tool called BPFlexTemplate, and tested it with the elicited variants

A concrete product derivation in software product line engineering: a practical approach

Software Product Lines enable the development of a perfect family of products by reusing shared assets in a systematic manner. Product derivation is a critical activity in software product line engineering and one of the most pressing issues that a software product line must address. This work introduces an approach for automating the derivation of a product from a software product line. The software product line is part of a product family that evolved from a non-structured approach to managing variability. The automated derivation approach relies on product configurations and the refactoring of feature models. The approach was deployed and evaluated in the automotive domain using a real-world software product line. The outcome demonstrates that the approach generates a product in an automated and successful manner.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020