Investigating the process of process modeling and its relation to modeling quality : the role of structured serialization

Lately, the focus of organizations is changing fundamentally. Where they used to spend almost exclusively attention to results, in terms of goods, services, revenue and costs, they are now concerned about the efficiency of their business processes. Each step of the business processes needs to be known, controlled and optimized. This explains the huge effort that many organizations currently put into the mapping of their processes in so-called (business) process models. Unfortunately, sometimes these models do not (completely) reflect the business reality or the reader of the model does not interpret the represented information as intended. Hence, whereas on the one hand we observe how organizations are attaching increasing importance to these models, on the other hand we notice how the quality of process models in companies often proves to be insufficient. The doctoral research makes a significant contribution in this context. This work investigates in detail how people create process models and why and when this goes wrong. A better understanding of current process modeling practice will form the basis for the development of concrete guidelines that result in the construction of better process models in the future. The first study investigated how we can represent the approach of different modelers in a cognitive effective way, in order to facilitate knowledge building. For this purpose the PPMChart was developed. It represents the different operations of a modeler in a modeling tool in such a way that patterns in their way of working can be detected easily. Through the collection of 704 unique modeling executions (a joint contribution of several authors in the research domain), and through the development of a concrete implementation of the visualization, it became possible to gather a great amount of insights about how different people work in different situations while modeling a concrete process. The second study explored, based on the discovered modeling patterns of the first study, the potential relations between how process models were being constructed and which quality was delivered. To be precise, three modeling patterns from the previous study were investigated further in their relation with the understandability of the produced process model. By comparing the PPMCharts that show these patterns with corresponding process models, a connection was found in each case. It was noticed that when a process model was constructed in consecutive blocks (i.e., in a structured way), a better understandable process model was produced. A second relation stated that modelers who (frequently) moved (many) model elements during modeling usually created a less understandable model. The third connection was found between the amount of time spent at constructing the model and a declining understandability of the resulting model. These relations were established graphically on paper, but were also confirmed by a simple statistical analysis. The third study selected one of the relations from the previous study, i.e., the relation between structured modeling and model quality, and investigated this relation in more detail. Again, the PPMChart was used, which has lead to the identification of different ways of structured process modeling. When a task is difficult, people will spontaneously split up this task in sub-tasks that are executed consecutively (instead of simultaneously). Structuring is the way in which the splitting of tasks is handled. It was found that when this happens consistently and according to certain logic, modeling became more effective and more efficient. Effective because a process model was created with less syntactic and semantic errors and efficient because it took less time and modeling operations. Still, we noticed that splitting up the modeling in sub-tasks in a structured way, did not always lead to a positive result. This can be explained by some people structuring the modeling in the wrong way. Our brain has cognitive preferences that cause certain ways of working not to fit. The study identified three important cognitive preferences: does one have a sequential or a global learning style, how context-dependent one is and how big one’s desire and need for structure is. The Structured Process Modeling Theory was developed, which captures these relations and which can form the basis for the development of an optimal individual approach to process modeling. In our opinion the theory has the potential to also be applicable in a broader context and to help solving various types of problems effectively and efficiently

Managing Consistency of Business Process Models across Abstraction Levels

Process models support the transition from business requirements to IT implementations. An organization that adopts process modeling often maintain several co-existing models of the same business process. These models target different abstraction levels and stakeholder perspectives. Maintaining consistency among these models has become a major challenge for such an organization. For instance, propagating changes requires identifying tacit correspondences among the models, which may be only in the memories of their original creators or may be lost entirely. Although different tools target specific needs of different roles, we lack appropriate support for checking whether related models maintained by different groups of specialists are still consistent after independent editing. As a result, typical consistency management tasks such as tracing, differencing, comparing, refactoring, merging, conformance checking, change notification, and versioning are frequently done manually, which is time-consuming and error-prone. This thesis presents the Shared Model, a framework designed to improve support for consistency management and impact analysis in process modeling. The framework is designed as a result of a comprehensive industrial study that elicited typical correspondence patterns between Business and IT process models and the meaning of consistency between them. The framework encompasses three major techniques and contributions: 1) matching heuristics to automatically discover complex correspondences patterns among the models, and to maintain traceability among model parts---elements and fragments; 2) a generator of edit operations to compute the difference between process models; 3) a process model synchronizer, capable of consistently propagating changes made to any model to its counterpart. We evaluated the Shared Model experimentally. The evaluation shows that the framework can consistently synchronize Business and IT views related by correspondence patterns, after non-simultaneous independent editing

Automatisches Zeichnen von Graphen für modellgetriebene Softwareentwicklung

As shown previously by Fuhrmann, there are several concepts for increasing the productivity of MDE by improving the practical handling of models. The automatic layout of graph-based models is a key enabler in this context. However, there is a striking contrast between the abundance of research results in the field of graph layout methods and the current state of graphical modeling tools, where only a tiny fraction of these results are ever adopted. This thesis aims to bridge this gap on three separate levels: specialized layout algorithms, configuration management, and software infrastructure. Regarding layout algorithms, here we focus on the layer-based approach. We examine its extension to include ports and hyperedges, which are essential features of certain kinds of graphs, e.g. data flow models. The main contribution is the handling of constraints on the positioning of ports, which is done mainly in the crossing minimization and edge routing phases. Hyperedges are represented with normal edges, simplifying their handling but introducing inaccuracies for counting crossings. A final extension discussed here is a sketch-driven approach for simple integration of user interactivity. An abstract layout is the selection of a layout algorithm with a mapping of its parameters to specific values. We discuss a new meta model allowing to specify the structure of a graph as well as its abstract layout and its concrete layout, i.e. positioning data computed by the layout algorithm. This forms a basis for efficient management of layout configurations. Furthermore, we investigate an evolutionary algorithm for searching the solution space of abstract layouts, taking readability criteria into account for evaluating solutions. The software infrastructure developed here targets the connection of arbitrary diagram viewers (front-ends) with arbitrary graph layout algorithms (back-ends). The main challenge is to find suitable abstractions that allow such generality and at the same time keep the complexity as low as possible. We discuss a possible realization based on the Eclipse platform, which is used by several modeling tools, e.g. the Graphical Modeling Framework. A web-based survey has been conducted among users of the layout infrastructure in order to evaluate to what extent the stated goals have been met. The overall feedback collected from this survey is very positive.Wie bereits von Fuhrmann gezeigt, kann die Produktivität modellgetriebener Softwareentwicklung durch zahlreiche Konzepte zur Verbesserung der praktischen Handhabung von Modellen erhöht werden. Dabei ist das automatische Layout graphenbasierter Modelle ein zentraler Schlüssel. Allerdings gibt es einen bemerkenswerten Kontrast zwischen der Fülle an Forschungsergebnissen im Bereich des Graphen-Layout und dem aktuellen Stand graphischer Modellierungswerkzeuge, bei denen nur ein kleiner Teil dieser Ergebnisse übernommen wird. Das Ziel dieser Arbeit ist diese Lücke auf drei separaten Ebenen zu überbrücken: spezialisierte Layout-Algorithmen, Verwaltung von Konfigurationen und Software-Infrastruktur. Im Bezug auf Layout-Algorithmen liegt der Schwerpunkt auf dem Layer-basierten Ansatz. Wir untersuchen dessen Erweiterung zur Unterstützung von Ports und Hyperkanten, was wesentliche Bestandteile bestimmter Arten von Graphen sind, z.B. Datenflussmodelle. Der Hauptbeitrag ist die Einbeziehung von Bedingungen für die Positionierung von Ports, vor allem während der Kreuzungsminimierung und der Kantenführungsphase. Hyperkanten werden durch normale Kanten repräsentiert, was deren Verarbeitung vereinfacht aber Ungenauigkeiten beim Zählen von Kreuzungen verursacht. Als letzte Erweiterung betrachten wir einen Sketch-basierten Ansatz für die einfache Integration von Nutzerinteraktivität. Ein abstraktes Layout ist die Auswahl eines Layout-Algorithmus zusammen mit einer Abbildung seiner Parameter auf konkrete Werte, während ein konkretes Layout Positionsdaten beschreibt, die von einem Algorithmus berechnet wurden. Wir diskutieren ein neues Metamodell, mit dem sowohl die Struktur als auch das abstrakte sowie das konkrete Layout eines Graphen spezifiziert werden kann. Dies bildet eine Grundlage für die effiziente Verwaltung von Layout-Konfigurationen. Zudem untersuchen wir einen evolutionären Algorithmus für die Suche im Lösungsraum abstrakter Layouts, wobei zur Bewertung von Lösungen Ästhetikkriterien ausgewertet werden. Die in dieser Arbeit entwickelte Software-Infrastruktur hat als Ziel, beliebige Graphen-basierte Diagramme (front-ends) mit beliebigen Layout-Algorithmen (back-ends) zu verbinden. Die größte Herausforderung dabei ist das Finden geeigneter Abstraktionen, die eine solche Allgemeingültigkeit erlauben und gleichzeitig die Komplexität so niedrig wie möglich halten. Wir betrachten eine mögliche Realisierung, die auf Eclipse basiert, eine von vielen Modellierungswerkzeugen verwendete Plattform. Eine Web-basierte Umfrage wurde unter Nutzern der Layout-Infrastruktur durchgeführt, um zu untersuchen inwieweit die gesteckten Ziele erfüllt worden sind. Die allgemeine Resonanz zu dieser Umfrage ist sehr positiv

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF