Enhancing declarative process models with DMN decision logic

Modeling dynamic, human-centric, non-standardized and knowledge-intensive business processes with imperative process modeling approaches is very challenging. Declarative process modeling approaches are more appropriate for these processes, as they offer the run-time flexibility typically required in these cases. However, by means of a realistic healthcare process that falls in the aforementioned category, we demonstrate in this paper that current declarative approaches do not incorporate all the details needed. More specifically, they lack a way to model decision logic, which is important when attempting to fully capture these processes. We propose a new declarative language, Declare-R-DMN, which combines the declarative process modeling language Declare-R with the newly adopted OMG standard Decision Model and Notation. Aside from supporting the functionality of both languages, Declare-R-DMN also creates bridges between them. We will show that using this language results in process models that encapsulate much more knowledge, while still offering the same flexibility

Optimized Time Management for Declarative Workflows

Declarative process models are increasingly used since they fit better with the nature of flexible process-aware information systems and the requirements of the stakeholders involved. When managing business processes, in addition, support for representing time and reasoning about it becomes crucial. Given a declarative process model, users may choose among different ways to execute it, i.e., there exist numerous possible enactment plans, each one presenting specific values for the given objective functions (e.g., overall completion time). This paper suggests a method for generating optimized enactment plans (e.g., plans minimizing overall completion time) from declarative process models with explicit temporal constraints. The latter covers a number of well-known workflow time patterns. The generated plans can be used for different purposes like providing personal schedules to users, facilitating early detection of critical situations, or predicting execution times for process activities. The proposed approach is applied to a range of test models of varying complexity. Although the optimization of process execution is a highly constrained problem, results indicate that our approach produces a satisfactory number of suitable solutions, i.e., solutions optimal in many cases

Requirements and Tools for Variability Management

Explicit and software-supported Business Process Management has become the core infrastructure of any medium and large organization that has a need to be efficient and effective. The number of processes of a single organization can be very high, furthermore, they might be very similar, be in need of momentary change, or evolve frequently. If the ad-hoc adaptation and customization of processes is currently the dominant way, it clearly is not the best. In fact, providing tools for supporting the explicit management of variation in processes (due to customization or evolution needs) has a profound impact on the overall life-cycle of processes in organizations. Additionally, with the increasing adoption of Service-Oriented Architectures, the infrastructure to support automatic reconfiguration and adaptation of business process is solid. In this paper, after defining variability in business process management, we consider the requirements for explicit variation handling for (service based) business process systems. eGovernment serves as an illustrative example of reuse. In this case study, all local municipalities need to implement the same general legal process while adapting it to the local business practices and IT infrastructure needs. Finally, an evaluation of existing tools for explicit variability management is provided with respect to the requirements identified.

Business Process Configuration According to Data Dependency Specification

Configuration techniques have been used in several fields, such as the design of business process models. Sometimes these models depend on the data dependencies, being easier to describe what has to be done instead of how. Configuration models enable to use a declarative representation of business processes, deciding the most appropriate work-flow in each case. Unfortunately, data dependencies among the activities and how they can affect the correct execution of the process, has been overlooked in the declarative specifications and configurable systems found in the literature. In order to find the best process configuration for optimizing the execution time of processes according to data dependencies, we propose the use of Constraint Programming paradigm with the aim of obtaining an adaptable imperative model in function of the data dependencies of the activities described declarative.Ministerio de Ciencia y Tecnología TIN2015-63502-C3-2-RFondo Europeo de Desarrollo Regiona

VERTO: a visual notation for declarative process models

Declarative approaches to business process modeling allow to represent loosely-structured (declarative) processes in flexible scenarios as a set of constraints on the allowed flow of activities. However, current graphical notations for declarative processes are difficult to interpret. As a consequence, this has affected widespread usage of such notations, by increasing the dependency on experts to understand their semantics. In this paper, we tackle this issue by introducing a novel visual declarative notation targeted to a more understandable modeling of declarative processes

Clinical Processes - The Killer Application for Constraint-Based Process Interactions?

For more than a decade, the interest in aligning information systems in a process-oriented way has been increasing. To enable operational support for business processes, the latter are usually specified in an imperative way. The resulting process models, however, tend to be too rigid to meet the flexibility demands of the actors involved. Declarative process modeling languages, in turn, provide a promising alternative in scenarios in which a high level of flexibility is demanded. In the scientific literature, declarative languages have been used for modeling rather simple processes or synthetic examples. However, to the best of our knowledge, they have not been used to model complex, real-world scenarios that comprise constraints going beyond control-flow. In this paper, we propose the use of a declarative language for modeling a sophisticated healthcare process scenario from the real world. The scenario is subject to complex temporal constraints and entails the need for coordinating the constraint-based interactions among the processes related to a patient treatment process. As demonstrated in this work, the selected real process scenario can be suitably modeled through a declarative approach.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-RMinisterio de Economía y Competitividad TIN2015-71938-RED

Model transformations in Converge

Model transformations are currently the focus of much interest and research due to the OMG’s QVT initiative. Current proposals for model transformation languages can be divided into two main camps: those taking a ‘declarative’ approach, and those opting for an ‘imperative’ approach. In this paper we detail an imperative, meta-circular, object orientated, pattern matching programming language Converge which is enriched with features pioneered by the Icon programming language, amongst them: success/failure, generators and goal-directed evaluation. By presenting these features in a language suitable for representing models, we show that we are able to gain some of the advantages of declarative approaches in an imperative setting