Open Access
ITM Web Conf.
Volume 60, 2024
2023 5th International Conference on Advanced Information Science and System (AISS 2023)
Article Number 00012
Number of page(s) 6
Published online 09 January 2024
  1. W. van der Aalst, Process Mining: Discovery, conformance and enhancement of business processes, Media; Springer: Berlin/Heidelberg, Germany, vol. 136, (2011). [Google Scholar]
  2. W. van der Aalst, Process mining: Overview and opportunities, ACM (TMIS), vol. 3, no. 2, pp. 1-17, (2012). [Google Scholar]
  3. B. van Dongen, Bpi challenge (2017), 2017. [Online]. Available: [Google Scholar]
  4. F. Mannhardt, M. De Leoni, H. A. Reijers, and W. M. Van Der Aalst, Data-driven process discovery revealing conditional infrequent behaviour from event logs, Advanced Information Systems Engineering: 29th International Conference, CAiSE 2017, Essen, Germany, June 12-16, (2017), Proceedings 29, pp. 545–560. [Google Scholar]
  5. M. Dees and B. van Dongen, Bpi challenge (2016): Clicks logged in 2016. [Online]. Available: [Google Scholar]
  6. W. M. Van Der Aalst and M. Pesic, Decserflow: Towards a truly declarative service flow language, Web Services and Formal Methods: Third International Workshop, WS-FM 2006 Vienna, Austria, September 8-9, 2006, Proceedings 3, pp. 1–23, 2006. [Google Scholar]
  7. A. Adriansyah, Aligning observed and modelled behaviour, Ph.D. dissertation, Mathematics and Computer Science, 2014, isbn: 978-90-3863574-3 [Google Scholar]
  8. C. Baier and J.-P. Katoen, Principles of model checking. MIT press, (2008). [Google Scholar]
  9. E.M. Clarke, F. Lerda, Model checking: Software and beyond. J. UCS (2007), 13, 639–649. [MathSciNet] [Google Scholar]
  10. M. Dumas, M. La Rosa, J. Mendling, H. A. Reijers, et al. Fundamentals of business process management; Vol. 2, Springer, (2018). [Google Scholar]
  11. W. van der Aalst, T. Weijters, L. Maruster, Workflow mining: Discovering process models from event logs. IEEE transactions on KDE (2004), 16, 1128–1142. [Google Scholar]
  12. W. van der Aalst, H.T. de Beer, B.F. van Dongen, Process mining and verification of properties: An approach based on temporal logic. On the Move to Meaningful Internet Systems (2005): CoopIS, DOA, and ODBASE: OTM Confederated International Conferences, CoopIS, DOA, and ODBASE 2005, Agia Napa, Cyprus, October 31 November 4, 2005, Proceedings, Part I (2005), pp. 130–147. [Google Scholar]
  13. M. Räim, C. Di Ciccio, F.M. Maggi, M. Mecella, J. Mendling, Log-based understanding of business processes through temporal logic query checking. On the Move to Meaningful Internet Systems: OTM (2014) Conferences: Confederated International Conferences: CoopIS, and ODBASE (2014), Amantea, Italy, October 27-31, 2014, Proceedings (2014), pp. 75–92. [Google Scholar]
  14. S. Morimoto, A survey of formal verification for business process modelling, International Conference on Computational Science, pp. 514-522, 2008. [Google Scholar]
  15. H. Groefsema and D. Bucur, A survey of formal business process verificationfrom soundness to variability, Third International Symposium on Business Modeling and Software Design, vol. 1, pp. 198–203, (2013). [Google Scholar]
  16. O. M. Kherbouche, A. Ahmad, and H. Basson, Formal approach for compliance rules checking in business process models, 2013 IEEE 9th International Conference on Emerging Technologies (ICET), pp. 1–6, (2013). [Google Scholar]
  17. S. Kripke, Semantical considerations on modal logic, Acta Philosophica Fennica, vol. 16, pp. 83–94, (1963). [Google Scholar]
  18. F. Corradini, F. Fornari, A. Polini, B. Re, F. Tiezzi, and A. Vandin, Bprove: A formal verification framework for business process models, 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE), pp. 217–228, (2017). [Google Scholar]
  19. F. A. Mangi, G. Su, and M. Zhang, Pm2pmc: A probabilistic model checking approach in process mining, 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET), pp. 1–6, (2023). [Google Scholar]
  20. F. A. Mangi, G. Su, and M. Zhang, Integrating process mining with probabilistic model checking via continuous time Markov chains, FCS’23 The 19th International Conference on Foundations of Computer Science July 24-27, 2023, pp. 1-6. (Proceedings to be published). [Google Scholar]
  21. R. Casaluce, A. Burattin, F. Chiaromonte, A. Vandin, Process Mining Meets Statistical Model Checking: Towards a Novel Approach to Model Validation and Enhancement. International Conference on Business Process Management (2022), pp. 243–256. [Google Scholar]
  22. M. Kwiatkowska, G. Norman, and D. Parker, Stochastic model checking, Formal Methods for Performance Evaluation: 7th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2007, Bertinoro, Italy, May 28-June 2, 2007, Advanced Lectures 7, pp. 220–270, (2007). [Google Scholar]
  23. Younes, H.L.S. Verification and planning for stochastic processes with asynchronous events, Carnegie Mellon University, (2004). [Google Scholar]
  24. K. Sen, M. Viswanathan, and G. Agha, On statistical model checking of stochastic systems, Computer Aided Verification: 17th International Conference, CAV 2005, Edinburgh, Scotland, UK, July 6-10, 2005. Proceedings 17, pp. 266–280, (2005). [Google Scholar]
  25. G. Agha and K. Palmskog, A survey of statistical model checking, ACM TOMACS, vol. 28, no. 1, pp. 1–39, (2018). [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.