Petri nets with may/must semantics: Preserving properties through data refinements

Many systems used in process managements, like workflow systems, are developed in a top-down fashion, when the original design is refined at each step bringing it closer to the underlying reality. Underdefined specifications cannot however be used for verification, since both false positives and false negatives can be reported. In this paper we introduce colored Petri nets where guards can be evaluated to true, false and indefinite values, the last ones reflecting underspecification. This results in the semantics of Petri nets with may- and must-enableness and firings. In this framework we introduce property-preserving refinements that allow for verification in an early design phase. We present results on property preservation through refinements. We also apply our framework to workflow nets, introduce notions of may- and must-soundness and show that they are preserved through refinements. We shortly describe a prototype under implementation

Analyzing control-flow and data-flow in workflow processes in a unified way

Workflow correctness properties are usually defined based on one workflow perspective only, e.g. the control-flow or the data-flow. In this paper we consider workflow correctness criteria looking at the control flow extended with the read/write/destroy information for data items. We formalize some common control-flow errors, and we introduce behavioral anti-patterns related to the handling of data. In addition to extending, refining, and classifying existing methods, our paper provides a unifying framework for complete workflow verification, using the well-known, stable, adaptable, and effective model-checking approach

Workflow completion patterns

The most common correctness requirement for a (business) workflow is the completion requirement, imposing that, in some form, every case-instance of the workflow reaches its final state. In this paper, we define three workflow completion patterns, called the mandatory, optional and possible completion. These patterns are formalized in terms of the temporal logic CTL*, to remove ambiguities, allow for easy comparison, and have direct applicability. In contrast to the existing methods, we do not look at the control flow in isolation but include some data information as well. In this way the analysis remains tractable but gains precision. Together with our previous work on data-flow (anti-)patterns, this paper is a significant step towards a unifying framework for complete workflow verification, using the well-developed, stable, adaptable, and effective model-checking approach

Branching bisimulation equivalence with explicit divergence

We consider the relational characterisation of branching bisimilarity with explicit divergence. We prove that it is an equivalence and that it coincides with the original definition of branching bisimilarity with explicit divergence in terms of coloured traces. We also establish a correspondence with several variants of an action-based modal logic with until- and divergence modalities

Strong, Weak and Branching Bisimulation for Transition Systems and Markov Reward Chains: A Unifying Matrix Approach

We first study labeled transition systems with explicit successful termination. We establish the notions of strong, weak, and branching bisimulation in terms of boolean matrix theory, introducing thus a novel and powerful algebraic apparatus. Next we consider Markov reward chains which are standardly presented in real matrix theory. By interpreting the obtained matrix conditions for bisimulations in this setting, we automatically obtain the definitions of strong, weak, and branching bisimulation for Markov reward chains. The obtained strong and weak bisimulations are shown to coincide with some existing notions, while the obtained branching bisimulation is new, but its usefulness is questionable

Process mining online assessment data

Traditional data mining techniques have been extensively applied to find interesting patterns, build descriptive and predictive models from large volumes of data accumulated through the use of different information systems. The results of data mining can be used for getting a better understanding of the underlying educational processes, for generating recommendations and advice to students, for improving management of learning objects, etc. However, most of the traditional data mining techniques focus on data dependencies or simple patterns and do not provide a visual representation of the complete educational (assessment) process ready to be analyzed. To allow for these types of analysis (in which the process plays the central role), a new line of data-mining research, called process mining, has been initiated. Process mining focuses on the development of a set of intelligent tools and techniques aimed at extracting process-related knowledge from event logs recorded by an information system. In this paper we demonstrate the applicability of process mining, and the ProM framework in particular, to educational data mining context. We analyze assessment data from recently organized online multiple choice tests and demonstrate the use of process discovery, conformance checking and performance analysis techniques

Energy saving potential of climate adaptive building shells - Inverse modelling of optimal thermal and visual behaviour

In common building design practice energy performance calculation programs or, in the best case, dynamic building simulation programs are used to optimize the properties of a building shell. However, even with use of dynamic building simulation programs adaptive behaviour, in terms of changing building shell properties, is not easy to simulate since many inputs - like insulation values, window ratio, etc. are ‘fixed’ values. The result of these optimization calculations is therefore rather an optimization in fixed design values then a set of ideal optimal adaptive behaviour building shell parameters. In the Dutch FACET project (Dutch acronym: ‘Adaptive façade technology for increased comfort and lower energy use in the future’) a quest for the ideal building shell with adaptive, variable properties is performed. Since the standard way of simulating does not allow fully adaptive building shell behaviour, a completely new, inverse modelling approach is set up. The key question here is: "What would be the ideal, dynamic properties of a building shell to get the desired indoor climate at variable outdoor climate conditions?" By reversing the design approach, and using inverse modelling, a set of ideal, hypothetical building shell parameters is computed for different climate conditions at various time steps (seasons, daynight, instantaneous), for different building categories like offices, schools and dwellings. This ‘ideal’ adaptive behaviour will make it possible to maximize indoor comfort and to minimize energy use for heating, cooling, ventilation and lighting. It does not start with having existing concepts in mind, but instead focuses on clarifying the theoretical potential of adaptive architecture. In the TRNSYS and Radiance simulations the building shell input is given as a black box, with a wide range of possible (combinations of) thermal and visual properties. Technologies and materials to meet the requirements can be more futuristic but also very ‘down to earth’. Partial solutions are already available, in low or high tech solutions, such as smart glazing, variable vacuum insulation, insulating window covering, etc. Further technology development is expected to be desired to fully meet the ideally adaptive behaviour requirements. Based on state of the art ‘adaptive temperature’ criteria optimal thermal behaviour was simulated in a first step. This gives the energy saving potential for an optimal thermal adaptive building shell. In a second step the computed optimal daylight characteristics of the building shell is given by optimizing visual comfort in Radiance. In a next step, both visual and thermal behaviour is optimized in an integral way, using a multi objective criteria approach. This paper describes the thermal and visual simulation optimization results of the FACET project. Preliminary results show that optimal adaptive building shell properties can reduce the total heating and cooling demand by a factor 10 compared to state of the art new built offices. For the Netherlands this means a factor 3 compared to the very efficient passive house technology. In the case of offices the heat demand is practically eliminated and the cooling demand can be reduced significantly by a factor two. The resulting extremely low energy demand means that less effort is needed to enable zero energy, or energy producing buildings in the future