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Non-Automata Based Conformance Checking of Declarative Process Specifications Based on ASP

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Business Process Management Workshops (BPM 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 492))

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Abstract

We investigate the use of Answer Set Programming (ASP) for the problem of conformance checking of LTL-based Declarative Process Specifications. In particular, we propose ASP solutions that are independent of automata. That is: in related works, the semantics of the declarative process specifications are often captured by means of finite state automata. This means that for conformance checking, the constraints of the specification first have to be transformed into a corresponding automata representation, which introduces a computational burden. In this work, we present a new ASP-based approach which encodes the constraint semantics directly and therefore can be used to check conformance without the need of performing automata operations. We implement our approach and perform experiments with real-life datasets, comparing our approach to a selection of state-of-the-art approaches. Our experiments show that our approach can outperform existing approaches in some cases. Furthermore, our approach can easily be extended to check whether the considered constraint sets are satisfiable (i.e., consistent).

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Notes

  1. 1.

    \(d(\varphi )\) is inductively defined via \(d(a)=0\) for \(a\in \textsf{At}\), \(d(\lnot \varphi )=d(\varphi )\), \(d(\varphi _1\wedge \varphi _2)=d(\varphi _1\vee \varphi _2)=\max \{d(\varphi _1),d(\varphi _2)\}\), \(d({\textbf {X}} \varphi )=1+d(\varphi )\), and \(d(\varphi _1 {\textbf {U}} \varphi _2)=1+\max \{d(\varphi _1),d(\varphi _2)\}\).

  2. 2.

    Recall that we assume time of a fixed length \(t_0,\ldots ,t_m\) and interpretations only vary in what is true at each state.

  3. 3.

    We will denote all sequences \(s=\langle s_0,\ldots ,s_m\rangle \in \textsf{At}^*\) as \(s_0\ldots s_m\) for readability, e.g., abc instead of \(\langle a,b,c\rangle \).

  4. 4.

    See for example [9] for an algorithm for this problem.

  5. 5.

    We refer the reader to [4] to further details on FSAs.

  6. 6.

    Note that we also use anonymous variables. Such variables, denoted by “_”, do not recur within the rule at hand.

  7. 7.

    For some years, e.g., 2020, there were multiple sub data sets - as these were similar, we only present the respective first sub data set of those years due to space reasons.

  8. 8.

    The implementation is available under https://e.feu.de/cc-asp.

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Author information

Authors and Affiliations

  1. Artificial Intelligence Group, University of Hagen, Hagen, Germany

    Isabelle Kuhlmann

  2. Institute for IS Research, University of Koblenz, Koblenz, Germany

    Carl Corea

  3. Department of Computer Science and UMIACS, University of Maryland, College Park, USA

    John Grant

Authors
  1. Isabelle Kuhlmann
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  2. Carl Corea
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  3. John Grant
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Correspondence to Isabelle Kuhlmann .

Editor information

Editors and Affiliations

  1. KU Leuven, Leuven, Belgium

    Jochen De Weerdt

  2. TUM School of Computation, Information and Technology, Heilbronn, Germany

    Luise Pufahl

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Kuhlmann, I., Corea, C., Grant, J. (2024). Non-Automata Based Conformance Checking of Declarative Process Specifications Based on ASP. In: De Weerdt, J., Pufahl, L. (eds) Business Process Management Workshops. BPM 2023. Lecture Notes in Business Information Processing, vol 492. Springer, Cham. https://doi.org/10.1007/978-3-031-50974-2_30

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  • DOI: https://doi.org/10.1007/978-3-031-50974-2_30

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