Discovering Responsibilities with Dynamic Condition Response Graphs

  • Viktorija Nekrasaite
  • Andrew Tristan Parli
  • Christoffer Olling BackEmail author
  • Tijs Slaats
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11483)


Declarative process discovery is the art of using historical data to better understand the responsibilities of an organisation: its governing business rules and goals. These rules and goals can be described using declarative process notations, such as Dynamic Condition Response (DCR) Graphs, which has seen widespread industrial adoption within Denmark, in particular through its integration in a case management solution used by 70% of central government institutions. In this paper, we introduce ParNek: a novel, effective, and extensible miner for the discovery of DCR Graphs. We empirically evaluate ParNek and show that it significantly outperforms the state-of-the-art in DCR discovery and performs at least comparably to the state-of-the-art in Declare discovery. Notably, the miner can be configured to sacrifice relatively little precision in favour of significant gains in simplicity, making it the first miner able to produce understandable DCR Graphs for real-life logs.


Declarative process discovery Declarative models Dynamic Condition Response Graphs DCR Graphs DCR discovery 


  1. 1.
    Back, C.O., Debois, S., Slaats, T.: Towards an empirical evaluation of imperative and declarative process mining. In: Woo, C., Lu, J., Li, Z., Ling, T.W., Li, G., Lee, M.L. (eds.) ER 2018. LNCS, vol. 11158, pp. 191–198. Springer, Cham (2018). Scholar
  2. 2.
    Di Ciccio, C., Mecella, M.: On the discovery of declarative control flows for artful processes. ACM Trans. Manag. Inf. Syst. 5(4), 24:1–24:37 (2015)CrossRefGoogle Scholar
  3. 3.
    Debois, S., Hildebrandt, T., Slaats, T.: Hierarchical declarative modelling with refinement and sub-processes. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 18–33. Springer, Cham (2014). Scholar
  4. 4.
    Debois, S., Hildebrandt, T.T., Laursen, P.H., Ulrik, K.R.: Declarative process mining for DCR graphs. In: SAC 2017, pp. 759–764 (2017)Google Scholar
  5. 5.
    Debois, S., Hildebrandt, T.T., Slaats, T.: Replication, refinement & reachability: complexity in dynamic condition-response graphs. Acta Informatica 55(6), 489–520 (2018)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Debois, S., Slaats, T.: The analysis of a real life declarative process. In: 2015 IEEE Symposium Series on Computational Intelligence, pp. 1374–1382 (2015)Google Scholar
  7. 7.
    Goedertier, S., Martens, D., Vanthienen, J., Baesens, B.: Robust process discovery with artificial negative events. J. Mach. Learn. Res. 10(Jun), 1305–1340 (2009)MathSciNetzbMATHGoogle Scholar
  8. 8.
    Hildebrandt, T., Mukkamala, R.R., Slaats, T., Zanitti, F.: Contracts for cross-organizational workflows as timed dynamic condition response graphs. J. Logic Algebraic Program. (JLAP) 82, 164–185 (2013)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Hildebrandt, T.T., Mukkamala, R.R.: Declarative event-based workflow as distributed dynamic condition response graphs. In: PLACES (2010)Google Scholar
  10. 10.
    Hull, R., et al.: Introducing the guard-stage-milestone approach for specifying business entity lifecycles. In: Bravetti, M., Bultan, T. (eds.) WS-FM 2010. LNCS, vol. 6551, pp. 1–24. Springer, Heidelberg (2011). Scholar
  11. 11.
    Ly, L.T., Rinderle-Ma, S., Dadam, P.: Design and verification of instantiable compliance rule graphs in process-aware information systems. In: Pernici, B. (ed.) CAiSE 2010. LNCS, vol. 6051, pp. 9–23. Springer, Heidelberg (2010). Scholar
  12. 12.
    Maggi, F.M., Bose, R.P.J.C., van der Aalst, W.M.P.: Efficient discovery of understandable declarative process models from event logs. In: Ralyté, J., Franch, X., Brinkkemper, S., Wrycza, S. (eds.) CAiSE 2012. LNCS, vol. 7328, pp. 270–285. Springer, Heidelberg (2012). Scholar
  13. 13.
    Maggi, F.M., Mooij, A.J., van der Aalst, W.M.P.: User-guided discovery of declarative process models. In: 2011 IEEE Symposium on Computational Intelligence and Data Mining. IEEE (2011)Google Scholar
  14. 14.
    Object Management Group: Case Management Model and Notation, Version 1.0. Webpage, May 2014.
  15. 15.
    Pesic, M., van der Aalst, W.M.P.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM 2006. LNCS, vol. 4103, pp. 169–180. Springer, Heidelberg (2006). Scholar
  16. 16.
    Popova, V., Fahland, D., Dumas, M.: Artifact lifecycle discovery. Int. J. Coop. Inf. Syst. 24, 1550001 (2015)CrossRefGoogle Scholar
  17. 17.
    Schönig, S., Di Ciccio, C., Maggi, F.M., Mendling, J.: Discovery of multi-perspective declarative process models. In: Sheng, Q.Z., Stroulia, E., Tata, S., Bhiri, S. (eds.) ICSOC 2016. LNCS, vol. 9936, pp. 87–103. Springer, Cham (2016). Scholar
  18. 18.
    Slaats, T.: Flexible process notations for cross-organizational case management systems. PhD thesis, IT University of Copenhagen, January 2015Google Scholar
  19. 19.
    Slaats, T., Mukkamala, R.R., Hildebrandt, T., Marquard, M.: Exformatics declarative case management workflows as DCR graphs. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 339–354. Springer, Heidelberg (2013). Scholar
  20. 20.
    Van der Aalst, W., Adriansyah, A., van Dongen, B.: Replaying history on process models for conformance checking and performance analysis. Wiley Interdisc. Rev.: Data Min. Knowl. Discovery 2(2), 182–192 (2012)Google Scholar
  21. 21.
    Zeising, M., Schönig, S., Jablonski, S.: Towards a common platform for the support of routine and agile business processes. In: 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, October, pp. 94–103 (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Viktorija Nekrasaite
    • 1
  • Andrew Tristan Parli
    • 1
  • Christoffer Olling Back
    • 1
    Email author
  • Tijs Slaats
    • 1
  1. 1.Department of Computer ScienceUniversity of CopenhagenCopenhagen SDenmark

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