When Are Two Workflows the Same?

In the area of workflow management, one is confronted with a large number of competing languages and the relations between them (e.g. relative expressiveness) are usually not clear. Moreover, even within the same language it is generally possible to express the same workflow in different ways, a feature known as variability. This paper aims at providing some of the formal groundwork for studying relative expressiveness and variability by defining notions of equivalence capturing different views on how workflow systems operate. Firstly, a notion of observational equivalence in the absence of silent steps is defined and related to classical bisimulation. Secondly, a number of equivalence notions in the presence of silent steps are defined. A distinction is made between the case where silent steps are visible (but not controllable) by the environment and the case where silent steps are not visible, i.e., there is an alternation between system events and environment interactions. It is shown that these notions of equivalence are different and do not coincide with classical notions of bisimulation with silent steps (e.g. weak and branching)

Petri nets for systems and synthetic biology

We give a description of a Petri net-based framework for modelling and analysing biochemical pathways, which uni¯es the qualita- tive, stochastic and continuous paradigms. Each perspective adds its con- tribution to the understanding of the system, thus the three approaches do not compete, but complement each other. We illustrate our approach by applying it to an extended model of the three stage cascade, which forms the core of the ERK signal transduction pathway. Consequently our focus is on transient behaviour analysis. We demonstrate how quali- tative descriptions are abstractions over stochastic or continuous descrip- tions, and show that the stochastic and continuous models approximate each other. Although our framework is based on Petri nets, it can be applied more widely to other formalisms which are used to model and analyse biochemical networks

Heuristic Approaches for Generating Local Process Models through Log Projections

Local Process Model (LPM) discovery is focused on the mining of a set of process models where each model describes the behavior represented in the event log only partially, i.e. subsets of possible events are taken into account to create so-called local process models. Often such smaller models provide valuable insights into the behavior of the process, especially when no adequate and comprehensible single overall process model exists that is able to describe the traces of the process from start to end. The practical application of LPM discovery is however hindered by computational issues in the case of logs with many activities (problems may already occur when there are more than 17 unique activities). In this paper, we explore three heuristics to discover subsets of activities that lead to useful log projections with the goal of speeding up LPM discovery considerably while still finding high-quality LPMs. We found that a Markov clustering approach to create projection sets results in the largest improvement of execution time, with discovered LPMs still being better than with the use of randomly generated activity sets of the same size. Another heuristic, based on log entropy, yields a more moderate speedup, but enables the discovery of higher quality LPMs. The third heuristic, based on the relative information gain, shows unstable performance: for some data sets the speedup and LPM quality are higher than with the log entropy based method, while for other data sets there is no speedup at all.Comment: paper accepted and to appear in the proceedings of the IEEE Symposium on Computational Intelligence and Data Mining (CIDM), special session on Process Mining, part of the Symposium Series on Computational Intelligence (SSCI

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

A Petri Net approach for representing Orthogonal Variability Models

The software product line (SPL) paradigm is used for developing software system products from a set of reusable artifacts, known as platform. The Orthogonal Variability Modeling (OVM) is a technique for representing and managing the variability and composition of those artifacts for deriving products in the SPL. Nevertheless, OVM does not support the formal analysis of the models. For example, the detection of dead artifacts (i.e., artifcats that cannot be included in any product) is an exhaustive activity which implies the verification of relationships between artifacs, artifacts parents, and so on. In this work, we introduce a Petri nets approach for representing and analyzing OVM models. The proposed net is built from elemental topologies that represents OVM concepts and relationships. Finally, we simulate the net and study their properties in order to avoid the product feasibility problems.Fil: Martinez, Cristian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Leone, Horacio Pascual. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); ArgentinaFil: Gonnet, Silvio Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentin

BProVe: A formal verification framework for business process models

Business Process Modelling has acquired increasing relevance in software development. Available notations, such as BPMN, permit to describe activities of complex organisations. On the one hand, this shortens the communication gap between domain experts and IT specialists. On the other hand, this permits to clarify the characteristics of software systems introduced to provide automatic support for such activities. Nevertheless, the lack of formal semantics hinders the automatic verification of relevant properties. This paper presents a novel verification framework for BPMN 2.0, called BProVe. It is based on an operational semantics, implemented using MAUDE, devised to make the verification general and effective. A complete tool chain, based on the Eclipse modelling environment, allows for rigorous modelling and analysis of Business Processes. The approach has been validated using more than one thousand models available on a publicly accessible repository. Besides showing the performance of BProVe, this validation demonstrates its practical benefits in identifying correctness issues in real models