Mixing Paradigms for More Comprehensible Models

Petri nets efficiently model both data- and control-flow. Control-flow is either modeled explicitly as flow of a specific kind of data, or implicit based on the data-flow. Explicit modeling of control-flow is useful for well-known and highly structured processes, but may make modeling of abstract features of models, or processes which are highly dynamic, overly complex. Declarative modeling, such as is supported by Declare and DCR graphs, focus on control-flow, but does not specify it explicitly; instead specifications come in the form of constraints on the order or appearance of tasks. In this paper we propose a combination of the two, using colored Petri nets instead of plain Petri nets to provide full data support. The combined approach makes it possible to add a focus on data to declarative languages, and to remove focus from the explicit control-flow from Petri nets for dynamic or abstract processes. In addition to enriching both procedural processes in the form of Petri nets and declarative processes, we also support a flow from modeling only abstract data- and control-flow of a model towards a more explicit control-flow model if so desired. We define our combined approach, and provide considerations necessary for enactment. Our approach has been implemented in CPN Tools 4

Mixed-Paradigm Process Modeling with Intertwined State Spaces

Business process modeling often deals with the trade-off between comprehensibility and flexibility. Many languages have been proposed to support different paradigms to tackle these characteristics. Well-known procedural, token-based languages such as Petri nets, BPMN, EPC, etc. have been used and extended to incorporate more flexible use cases, however the declarative workflow paradigm, most notably represented by the Declare framework, is still widely accepted for modeling flexible processes. A real trade-off exists between the readable, rather inflexible procedural models, and the highly-expressive but cognitively demanding declarative models containing a lot of implicit behavior. This paper investigates in detail the scenarios in which combining both approaches is useful, it provides a scoring table for Declare constructs to capture their intricacies and similarities compared to procedural ones, and offers a step-wise approach to construct mixed-paradigm models. Such models are especially useful in the case of environments with different layers of flexibility and go beyond using atomic subprocesses modeled according to either paradigm. The paper combines Petri nets and Declare to express the findings

Object-oriented modelling with unified modelling language 2.0 for simple software application based on agile methodology

Unified modelling language (UML) 2.0 introduced in 2002 has been developing and influencing object-oriented software engineering and has become a standard and reference for information system analysis and design modelling. There are many concepts and theories to model the information system or software application with UML 2.0, which can make ambiguities and inconsistencies for a novice to learn to how to model the system with UML especially with UML 2.0. This article will discuss how to model the simple software application by using some of the diagrams of UML 2.0 and not by using the whole diagrams as suggested by agile methodology. Agile methodology is considered as convenient for novices because it can deliver the information technology environment to the end-user quickly and adaptively with minimal documentation. It also has the ability to deliver best performance software application according to the customer's needs. Agile methodology will make simple model with simple documentation, simple team and simple tools.Comment: 15 pages, 30 figure

Toward a Conceptualization of Mixed Methods Phenomenological Research

Increasingly, researchers are recognizing the benefits of expanding research designs that are rooted in one tradition (i.e., monomethod design) into a design that incorporates or interfaces with the other tradition. The flexibility of phenomenologically driven methods provides one such example. Indeed, phenomenological research methods work extremely well as a component of mixed methods research approaches. However, to date, a mixed methods version of phenomenological research has not been formally conceptualized. Thus, the purpose of this article is twofold. First, we provide a philosophical justification for using what we call mixed methods phenomenological research (MMPR). Second, we provide examples of MMPR in practice to underline a number of potential models for MMPR that can practically be used in future research

Strategic polymorphism requires just two combinators!

In previous work, we introduced the notion of functional strategies: first-class generic functions that can traverse terms of any type while mixing uniform and type-specific behaviour. Functional strategies transpose the notion of term rewriting strategies (with coverage of traversal) to the functional programming paradigm. Meanwhile, a number of Haskell-based models and combinator suites were proposed to support generic programming with functional strategies. In the present paper, we provide a compact and matured reconstruction of functional strategies. We capture strategic polymorphism by just two primitive combinators. This is done without commitment to a specific functional language. We analyse the design space for implementational models of functional strategies. For completeness, we also provide an operational reference model for implementing functional strategies (in Haskell). We demonstrate the generality of our approach by reconstructing representative fragments of the Strafunski library for functional strategies.Comment: A preliminary version of this paper was presented at IFL 2002, and included in the informal preproceedings of the worksho

CPN Tools 4 : a process modeling tool combining declarative and imperative paradigms

CPN Tools is a tool for modeling, simulating, and analyzing colored Petri nets. The latest iteration of the tool, CPN Tools 4, extends this with constraints known from declarative languages such as Declare and DCR Graphs. Furthermore, this version introduces an explicit process perspective, powerful extensibility allowing third parties to extend the tools capabilities, and a visualization perspective making it possible to make high-level visualizations of executions directly in the tool. In our demonstration, we show how it is possible to create models incorporating declarative and imperative constructs and how to use these models to generate simulation logs that can be directly imported into ProM. We show o¿ the new process perspective on top of colored Petri nets, exemplify the use of the perspective to generate readable Java code directly from models, and show how the visualization perspective makes it possible to show the formal underlying model alongside an easier-to-grasp for non-experts high-level visualization. Our intended audience comprise current users of CPN Tools interested in recent developments and practitioners interested in colored Petri nets and hybrid models. We expect to tailor each demonstration to the wishes of the audience

Making Complex Music with Simple Algorithms, is it Even Possible?

Algorithmic composition is often limited to score generation, but may also include sound production. All levels from sound synthesis to the generation of a complete composition can be integrated into one monolithic program. A strict separation of the low level of sound synthesis and higher levels otherwise reserved for algorithmic composition is not necessary, information can flow between all levels. An interesting challenge in this kind of thorough algorithmic composition is to generate as complex music as possible with as little code as possible. The challenge has been accepted, successfully or not, in a series of compositions called Kolmogorov Variations. We discuss the techniques used in a few of the pieces as well as the promises and perils of this strict approach to algorithmic composition

Making Complex Music with Simple Algorithms, is it Even Possible?

Algorithmic composition is often limited to score generation, but may also include sound production. All levels from sound synthesis to the generation of a complete composition can be integrated into one monolithic program. A strict separation of the low level of sound synthesis and higher levels otherwise reserved for algorithmic composition is not necessary, information can flow between all levels. An interesting challenge in this kind of thorough algorithmic composition is to generate as complex music as possible with as little code as possible. The challenge has been accepted, successfully or not, in a series of compositions called Kolmogorov Variations. We discuss the techniques used in a few of the pieces as well as the promises and perils of this strict approach to algorithmic composition

Declarative process modeling in BPMN

Traditional business process modeling notations, including the standard Business Process Model and Notation (BPMN), rely on an imperative paradigm wherein the process model captures all allowed activity flows. In other words, every flow that is not specified is implicitly disallowed. In the past decade, several researchers have exposed the limitations of this paradigm in the context of business processes with high variability. As an alternative, declarative process modeling notations have been proposed (e.g., Declare). These notations allow modelers to capture constraints on the allowed activity flows, meaning that all flows are allowed provided that they do not violate the specified constraints. Recently, it has been recognized that the boundary between imperative and declarative process modeling is not crisp. Instead, mixtures of declarative and imperative process modeling styles are sometimes preferable, leading to proposals for hybrid process modeling notations. These developments raise the question of whether completely new notations are needed to support hybrid process modeling. This paper answers this question negatively. The paper presents a conservative extension of BPMN for declarative process modeling, namely BPMN-D, and shows that Declare models can be transformed into readable BPMN-D models. © Springer International Publishing Switzerland 2015