Data Petri Nets meet Probabilistic Programming (Extended version)

Probabilistic programming (PP) is a programming paradigm that allows for writing statistical models like ordinary programs, performing simulations by running those programs, and analyzing and refining their statistical behavior using powerful inference engines. This paper takes a step towards leveraging PP for reasoning about data-aware processes. To this end, we present a systematic translation of Data Petri Nets (DPNs) into a model written in a PP language whose features are supported by most PP systems. We show that our translation is sound and provides statistical guarantees for simulating DPNs. Furthermore, we discuss how PP can be used for process mining tasks and report on a prototype implementation of our translation. We also discuss further analysis scenarios that could be easily approached based on the proposed translation and available PP tools.

Relational Action Bases: Formalization, Effective Safety Verification, and Invariants (Extended Version)

Modeling and verification of dynamic systems operating over a relational representation of states are increasingly investigated problems in AI, Business Process Management, and Database Theory. To make these systems amenable to verification, the amount of information stored in each relational state needs to be bounded, or restrictions are imposed on the preconditions and effects of actions. We introduce the general framework of relational action bases (RABs), which generalizes existing models by lifting both these restrictions: unbounded relational states can be evolved through actions that can quantify both existentially and universally over the data, and that can exploit numerical datatypes with arithmetic predicates. We then study parameterized safety of RABs via (approximated) SMT-based backward search, singling out essential meta-properties of the resulting procedure, and showing how it can be realized by an off-the-shelf combination of existing verification modules of the state-of-the-art MCMT model checker. We demonstrate the effectiveness of this approach on a benchmark of data-aware business processes. Finally, we show how universal invariants can be exploited to make this procedure fully correct.

Conformance Checking with Uncertainty via SMT (Extended Version)

Logs of real-life processes often feature uncertainty pertaining the recorded timestamps, data values, and/or events. We consider the problem of checking conformance of uncertain logs against data-aware reference processes. Specifically, we show how to solve it via SMT encodings, lifting previous work on data-aware SMT-based conformance checking to this more sophisticated setting. Our approach is modular, in that it homogeneously accommodates for different types of uncertainty. Moreover, using appropriate cost functions, different conformance checking tasks can be addressed. We show the correctness of our approach and witness feasibility through a proof-of-concept implementation.

Soundness in Object-centric Workflow Petri Nets

Recently introduced Petri net-based formalisms advocate the importance of proper representation and management of case objects as well as their co-evolution. In this work we build on top of one of such formalisms and introduce the notion of soundness for it. We demonstrate that for nets with non-deterministic synchronization between case objects, the soundness problem is decidable.

Monitoring Hybrid Process Specifications with Conflict Management: The Automata-theoretic Approach

Business process monitoring approaches have thus far mainly focused on monitoring the execution of a process with respect to a single process model. However, in some cases it is necessary to consider multiple process specifications simultaneously. In addition, these specifications can be procedural, declarative, or a combination of both. For example, in the medical domain, a clinical guideline describing the treatment of a specific disease cannot account for all possible co-factors that can coexist for a specific patient and therefore additional constraints may need to be considered. In some cases, these constraints may be incompatible with clinical guidelines, therefore requiring the violation of either the guidelines or the constraints. In this paper, we propose a solution for monitoring the interplay of hybrid process specifications expressed as a combination of (data-aware) Petri nets and temporal logic rules. During the process execution, if these specifications are in conflict with each other, it is possible to violate some of them. The monitoring system is equipped with a violation cost model according to which the system can recommend the next course of actions in a way that would either avoid possible violations or minimize the total cost of violations.

CoCoMoT: Conformance Checking of Multi-Perspective Processes via SMT (Extended Version)

Conformance checking is a key process mining task for comparing the expected behavior captured in a process model and the actual behavior recorded in a log. While this problem has been extensively studied for pure control-flow processes, conformance checking with multi-perspective processes is still at its infancy. In this paper, we attack this challenging problem by considering processes that combine the data and control-flow dimensions. In particular, we adopt data Petri nets (DPNs) as the underlying reference formalism, and show how solid, well-established automated reasoning techniques can be effectively employed for computing conformance metrics and data-aware alignments. We do so by introducing the CoCoMoT (Computing Conformance Modulo Theories) framework, with a fourfold contribution. First, we show how SAT-based encodings studied in the pure control-flow setting can be lifted to our data-aware case, using SMT as the underlying formal and algorithmic framework. Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering, to speed up the computation of conformance checking outputs. Third, we provide a proof-of-concept implementation that uses a state-of-the-art SMT solver and report on preliminary experiments. Finally, we discuss how CoCoMoT directly lends itself to a number of further tasks, like multi- and anti-alignments, log analysis by clustering, and model repair.

Formalizing Integration Patterns with Multimedia Data (Extended Version)

The previous works on formalizing enterprise application integration (EAI) scenarios showed an emerging need for setting up formal foundations for integration patterns, the EAI building blocks, in order to facilitate the model-driven development and ensure its correctness. So far, the formalization requirements were focusing on more "conventional" integration scenarios, in which control-flow, transactional persistent data and time aspects were considered. However, none of these works took into consideration another arising EAI trend that covers social and multimedia computing. In this work we propose a Petri net-based formalism that addresses requirements arising from the multimedia domain. We also demonstrate realizations of one of the most frequently used multimedia patterns and discuss which implications our formal proposal may bring into the area of the multimedia EAI development.

Petri Nets with Parameterised Data: Modelling and Verification (Extended Version)

During the last decade, various approaches have been put forward to integrate business processes with different types of data. Each of such approaches reflects specific demands in the whole process-data integration spectrum. One particular important point is the capability of these approaches to flexibly accommodate processes with multiple cases that need to co-evolve. In this work, we introduce and study an extension of coloured Petri nets, called catalog-nets, providing two key features to capture this type of processes. On the one hand, net transitions are equipped with guards that simultaneously inspect the content of tokens and query facts stored in a read-only, persistent database. On the other hand, such transitions can inject data into tokens by extracting relevant values from the database or by generating genuinely fresh ones. We systematically encode catalog-nets into one of the reference frameworks for the (parameterised) verification of data and processes. We show that fresh-value injection is a particularly complex feature to handle, and discuss strategies to tame it. Finally, we discuss how catalog nets relate to well-known formalisms in this area.