Execution of Multi-perspective Declarative Process Models

Ackermann, Lars; Schönig, Stefan; Petter, Sebastian; Schützenmeier, Nicolai; Jablonski, Stefan

doi:10.1007/978-3-030-02671-4_9

Cited by 15 publications

(36 citation statements)

References 21 publications

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“…We consider that σ t 1 5 is valid, but after submitting the paper (σ t 2 5 ) the trace becomes temporary invalid, because after submitting paper and abstract a check of the paper is mandatory. Executing the activity CheckPaper (σ t 3 5 ) changes the validity of the trace into valid again. Hence, one of the key challenges is to recognize whether an invalid uncompleted trace stays invalid or not.…”

Section: Challenge 1: Large Number Of Possible Process Trajectoriesmentioning

confidence: 99%

“…Therefore, we describe an Alloy-based meta-model (socalled Process Event Chain Meta-Model). This meta-model was proposed in [2] and extended in [3] to support the data-oriented perspective. We adapt this meta-model from a previous version [3] to support also the operational perspective.…”

Section: Transformation To Alloymentioning

confidence: 99%

“…The look-ahead determines all possible process trajectories up to a desired length based on an uncompleted process execution. While execution engines for single-perspective imperative process models already implement such functionality, execution approaches, for multi-perspective declarative process models that involve constraints on data and resources are less mature and do not consider preventive strategies [3].…”

Section: Introductionmentioning

confidence: 99%

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Language-independent look-ahead for checking multi-perspective declarative process models

et al. 2021

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Declarative process modelling languages focus on describing a process by restrictions over the behaviour, which must be satisfied throughout the whole process execution. Hence, they are well suited for modelling knowledge-intensive processes with many decision points. However, such models can be hard to read and understand, which affect the modelling and maintenance of the process models tremendously as well as their execution. When executing such declarative (multi-perspective) process models, it may happen that the execution of activities or the change of data values may result in the non-executability of crucial activities. Hence, it would be beneficial to know all consequences of decisions to give recommendations to the process participants. A look-ahead attempts to predict the effects of executing an activity towards possible consequences within an a priori defined time window. The prediction is based on the current state of the process execution, the intended next event and the underlying process model. While execution engines for single-perspective imperative process models already implement such functionality, execution approaches, for multi-perspective declarative process models that involve constraints on data and resources, are less mature. In this paper, we introduce a simulation-based look-ahead approach for multi-perspective declarative process models. This approach transforms the problem of a context-aware process simulation into a SAT problem, by translating a declarative multi-perspective process model and the current state of a process execution into a specification of the logic language Alloy. Via a SAT solver, process trajectories are generated that either satisfy or violate this specification. The simulated process trajectories are used to derive consequences and effects of certain decisions at any time of process execution. We evaluate our approach by means of three examples and give some advice for further optimizations.

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Section: Challenge 1: Large Number Of Possible Process Trajectoriesmentioning

confidence: 99%

Section: Transformation To Alloymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Language-independent look-ahead for checking multi-perspective declarative process models

et al. 2021

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“…As outlined in [16], the declarative process modeling approach can serve as a promising alternative paradigm for specifying event-driven IoT-based processes. Therefore, we will investigate and evaluate how IoT-aware processes can be defined, executed and analyzed by existing multi-perspective declarative process technology [46] or how other (declarative) standards like Case Management Model and Notation (CMMN) [47,48] can be adjusted to be used in IoT scenarios. In addition, it is necessary to implement different concepts for a more efficient and secure communication between objects.…”

Section: Conclusion Implications and Future Workmentioning

confidence: 99%

IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution

et al. 2020

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Business processes are frequently executed within application systems that involve humans, computer systems as well as objects of the Internet of Things (IoT). Nevertheless, the usage of IoT technology for system supported process execution is still constrained by the absence of a common system architecture that manages the communication between both worlds. In this paper, we introduce an integrated approach for IoT-aware business process execution that exploits IoT for BPM by providing IoT data in a process-compatible way, providing an IoT data provenance framework, considering IoT data for interaction in a pre-defined process model, and providing wearable user interfaces with context-specific IoT data provision. The approach has been implemented on top of contemporary BPM modeling concepts and system technology. The introduced technique has evaluated extensively in different use cases in industry.

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“…Furthermore, MP-Declare models are supported in the context of conformance checking [35], trace generation [36] and execution [37]. The execution engine builds on a classification strategy for different constraint types and a transformation component into the execution language Alloy that is used to solve SAT problems.…”

Section: Related Workmentioning

confidence: 99%

Full Support for Efficiently Mining Multi-Perspective Declarative Constraints from Process Logs

2019

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Declarative process management has emerged as an alternative solution for describing flexible workflows. In turn, the modelling opportunities with languages such as Declare are less intuitive and hard to implement. The area of process discovery covers the automatic discovery of process models. It has been shown that the performance of process mining algorithms, particularly when considering the multi-perspective declarative process models, are not satisfactory. State-of-the-art mining tools do not support multi-perspective declarative models at this moment. We address this open research problem by proposing an efficient mining framework that leverages the latest big data analysis technology and builds upon the distributed processing method MapReduce. The paper at hand further completes the research on multi-perspective declarative process mining by extending our previous work in various ways; in particular, we introduce algorithms and descriptions for the full set of commonly accepted types of MP-Declare constraints. Additionally, we provide a novel implementation concept allowing an easy introduction and discovery of customised constraint templates. We evaluated the mining performance and effectiveness of the presented approach on several real-life event logs. The results highlight that, with our efficient mining technique, multi-perspective declarative process models can be extracted in reasonable time.

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Execution of Multi-perspective Declarative Process Models

Cited by 15 publications

References 21 publications

Language-independent look-ahead for checking multi-perspective declarative process models

Language-independent look-ahead for checking multi-perspective declarative process models

IoT meets BPM: a bidirectional communication architecture for IoT-aware process execution

Full Support for Efficiently Mining Multi-Perspective Declarative Constraints from Process Logs

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