@article{HaarmannHolfterPufahletal.2021,
  author    = {Haarmann, Stephan and Holfter, Adrian and Pufahl, Luise and Weske, Mathias},
  title     = {Formal framework for checking compliance of data-driven case management},
  series = {Journal on data semantics : JoDS},
  volume    = {10},
  journal   = {Journal on data semantics : JoDS},
  number    = {1-2},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1861-2032},
  doi       = {10.1007/s13740-021-00120-3},
  pages     = {143 -- 163},
  year      = {2021},
  abstract  = {Business processes are often specified in descriptive or normative models. Both types of models should adhere to internal and external regulations, such as company guidelines or laws. Employing compliance checking techniques, it is possible to verify process models against rules. While traditionally compliance checking focuses on well-structured processes, we address case management scenarios. In case management, knowledge workers drive multi-variant and adaptive processes. Our contribution is based on the fragment-based case management approach, which splits a process into a set of fragments. The fragments are synchronized through shared data but can, otherwise, be dynamically instantiated and executed. We formalize case models using Petri nets. We demonstrate the formalization for design-time and run-time compliance checking and present a proof-of-concept implementation. The application of the implemented compliance checking approach to a use case exemplifies its effectiveness while designing a case model. The empirical evaluation on a set of case models for measuring the performance of the approach shows that rules can often be checked in less than a second.},
  language  = {en}
}