Many organizations use business process management to manage and model their processes. Currently, flow-based process formalisms, such as BPMN, are considered the standard for modeling processes. However, recent literature describes several limitations of this type of formalism that can be solved by adopting a constraint-based formalism. To preserve economic investments in existing process models, transformation activities needed to be limited. This paper presents a methodical approach for performing the tedious parts of process model transformation. Executing the method results in correctly transformed process models and reduces the effort required for converting the process models.
Organizations are struggling to choose from or combine the different business process management paradigms offered in today's BPM landscape, such as workflow management, dynamic case management and straight through processing. The field of declarative processes seems to be able to address this challenge by offering a unified approach to business process modeling, providing variable amounts of flow at execution time and different levels of autonomy to the actors based on models using a single formalism. The notion of declarativity in business processes seems to be ill defined and is often treated as a black and white distinction. However, a number of quite different formalisms have been developed that are broadly agreed to be declarative. This paper proposes a number of qualitative characteristics to characterize the declarative nature of process modeling formalisms. The characteristics are evaluated by applying them to a number of relevant process modeling formalisms, both imperative and declarative, and we discuss how these characteristics can be utilized to create business processes that offer activity flows that are known up front where needed, and allow ad hoc approaches to offer experts freedom and to support impediment driven approaches in an STP context.
Grammar-based procedural level generation raises the productivity of level designers for games such as dungeon crawl and platform games. However, the improved productivity comes at cost of level quality assurance. Authoring, improving and maintaining grammars is difficult because it is hard to predict how each grammar rule impacts the overall level quality, and tool support is lacking. We propose a novel metric called Metric of Added Detail (MAD) that indicates if a rule adds or removes detail with respect to its phase in the transformation pipeline, and Specification Analysis Reporting (SAnR) for expressing level properties and analyzing how qualities evolve in level generation histories. We demonstrate MAD and SAnR using a prototype of a level generator called Ludoscope Lite. Our preliminary results show that problematic rules tend to break SAnR properties and that MAD intuitively raises flags. MAD and SAnR augment existing approaches, and can ultimately help designers make better levels and level generators.
