Nicolai Schützenmeier

dblp:228/0710 · DBLP profile ↗
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5ranked-venue papers
4as first author
3since 2021 · last 2023
0009-0007-9967-0571ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 3 · 3 first-author · 2 since 2021Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2023 Automaton-based comparison of Declare process models
abstract
Abstract The Declare process modeling language has been established within the research community for modeling so-called flexible processes. Declare follows the declarative modeling paradigm and therefore guarantees flexible process execution. For several reasons, declarative process models turned out to be hard to read and comprehend. Thus, it is also hard to decide whether two process models are equal with respect to their semantic meaning, whether one model is completely contained in another one or how far two models overlap. In this paper, we follow an automaton-based approach by transforming Declare process models into finite state automatons and applying automata theory for solving this issue.
Nicolai Schützenmeier, Martin Käppel, Lars Ackermann, Stefan Jablonski, Sebastian Petter
Softw. Syst. Model.1
2023 Correction: Automaton-based comparison of Declare process models
abstract
models to finite state automatons
Nicolai Schützenmeier, Martin Käppel, Lars Ackermann, Stefan Jablonski, Sebastian Petter
Softw. Syst. Model.1
2021 Towards a Hybrid Process Modeling Language
Nicolai Schützenmeier, Stefan Jablonski, Stefan Schönig
RCIS1
2019 Detection of Declarative Process Constraints in LTL Formulas
Nicolai Schützenmeier, Martin Käppel, Sebastian Petter, Stefan Schönig, Stefan Jablonski
EOMAS@CAiSE1
2019 A Comparative Study for the Selection of Machine Learning Algorithms based on Descriptive Parameters
Chettan Kumar, Martin Käppel, Nicolai Schützenmeier, Philipp Eisenhuth, Stefan Jablonski
DATA3