Detection of Declarative Process Constraints in LTL Formulas
- 109 Downloads
Abstract
Declarative process models consist of temporal constraints that a process must satisfy during execution. Constraint templates are patterns that define parameterized classes of properties. Their semantics can be formalized using formal logics such as Linear Temporal Logic (LTL) over finite traces. There exists a big amount of different constraint templates for different purposes. In practice, the variety of different templates yields complexity and performance issues with regard to model comparison, compliance checking and in particular process mining. In this paper we give a comprehensively overview about existing declare templates and transform their underlying LTL formula into the positive normal form (PNF), a canonical standard form for LTL formulas. On this basis, we present an algorithm for detecting declare templates in any LTL formula fulfilling the conditions for PNF. We reduce the number of process constraints that have to be proven by the algorithm to speed up the runtime and give some advice for further optimizations.
Keywords
Declarative process management Declare Linear temporal logic Positive normal formReferences
- 1.Dumas, M., Rosa, M.L., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management, 2nd edn. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-662-56509-4CrossRefGoogle Scholar
- 2.Pesic, M., Schonenberg, H., van der Aalst, W.M.P.: Declare: full support for loosely-structured processes. In: IEEE EDOC Conference 2007, pp. 287–300 (2007)Google Scholar
- 3.Hildebrandt, T.T., Mukkamala, R.R., Slaats, T., Zanitti, F.: Contracts for cross-organizational workflows as timed dynamic condition response graphs. J. Log. Algebr. Program. 82(5–7), 164–185 (2013)MathSciNetCrossRefGoogle Scholar
- 4.Schönig, S., Ackermann, L., Jablonski, S.: Towards an implementation of data and resource patterns in constraint-based process models. In: Modelsward, pp. 271–278 (2018)Google Scholar
- 5.Zeising, M., Schönig, S., Jablonski, S.: Towards a common platform for the support of routine and agile business processes. In: Collaborative Computing: Networking, Applications and Worksharing (2014)Google Scholar
- 6.Maggi, F.M., Mooij, A., van der Aalst, W.: User-guided discovery of declarative process models. In: CIDM, pp. 192–199 (2011)Google Scholar
- 7.De Smedt, J., Weerdt, J., Vanthienen, J., Poels, G.: Mixed-paradigm process modeling with intertwined state spaces. Bus. Inf. Syst. Eng. 58, 12 (2015)Google Scholar
- 8.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). https://doi.org/10.1007/11837862_18CrossRefGoogle Scholar
- 9.Baier, C., Katoen, J.-P.: Principles of Model Checking. Representation and Mind Series. The MIT Press, Cambridge (2008)zbMATHGoogle Scholar
- 10.Emerson, E.A.: Temporal and modal logic. In: Formal Models and Semantics, pp. 995–1072. Elsevier (1990)Google Scholar
- 11.Fornara, N., Colombetti, M.: Specifying artificial institutions in the event calculus. In: Handbook of Research on Multi-agent Systems: Semantics and Dynamics of Organizational Models, pp. 335–366. IGI Global (2009)Google Scholar
- 12.Pesic, M., Schonenberg, H., Van der Aalst, W.M.: Declare: full support for loosely-structured processes. In: 11th IEEE International Enterprise Distributed Object Computing Conference (EDOC 2007), p. 287. IEEE (2007)Google Scholar
- 13.Bernardi, M.L., Cimitile, M., Di Francescomarino, C., Maggi, F.M.: Using discriminative rule mining to discover declarative process models with non-atomic activities. In: Bikakis, A., Fodor, P., Roman, D. (eds.) RuleML 2014. LNCS, vol. 8620, pp. 281–295. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-09870-8_21CrossRefGoogle Scholar
- 14.Baumann, M., Baumann, M.H., Schönig, S., Jablonski, S.: Resource-aware process model similarity matching. In: ICSOC 2014 Workshops, pp. 96–107 (2014)CrossRefGoogle Scholar
- 15.Lamma, E., Mello, P., Riguzzi, F., Storari, S.: Applying inductive logic programming to process mining. In: Inductive Logic Programming, pp. 132–146 (2007)Google Scholar
- 16.Chesani, F., Lamma, E., Mello, P., Montali, M., Riguzzi, F., Storari, S.: Exploiting inductive logic programming techniques for declarative process mining. In: Jensen, K., van der Aalst, W.M.P. (eds.) Transactions on Petri Nets and Other Models of Concurrency II. LNCS, vol. 5460, pp. 278–295. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-00899-3_16CrossRefGoogle Scholar
- 17.Westergaard, M., Maggi, F.M.: Looking into the future: using timed automata to provide a priori advice about timed declarative process models. In: Meersman, R., et al. (eds.) OTM 2012, Part I. LNCS, vol. 7565, pp. 250–267. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33606-5_16CrossRefGoogle Scholar
- 18.Montali, M., Chesani, F., Mello, P., Maggi, F.M.: Towards data-aware constraints in declare. In: SAC, pp. 1391–1396. ACM (2013)Google Scholar
- 19.Burattin, A., Maggi, F.M., Sperduti, A.: Conformance checking based on multi-perspective declarative process models. Expert Syst. Appl. 65, 194–211 (2016)CrossRefGoogle Scholar
- 20.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). https://doi.org/10.1007/978-3-319-46295-0_6CrossRefGoogle Scholar
- 21.Ackermann, L., Schönig, S., Jablonski, S.: Simulation of multi-perspective declarative process models. In: Dumas, M., Fantinato, M. (eds.) BPM 2016. LNBIP, vol. 281, pp. 61–73. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58457-7_5CrossRefGoogle Scholar
- 22.Skydanienko, V., Francescomarino, C.D., Maggi, F.: A tool for generating event logs from multi-perspective declare models. In: BPM (Demos) (2018)Google Scholar
- 23.Ackermann, L., Schönig, S., Petter, S., Schützenmeier, N., Jablonski, S.: Execution of multi-perspective declarative process models. In: OTM 2018 Conferences, pp. 154–172 (2018)Google Scholar
- 24.van der Aalst, W., Pesic, M., Schonenberg, H.: Declarative workflows: balancing between flexibility and support. In: CSRD, pp. 99–113 (2009)Google Scholar
- 25.Montali, M., Pesic, M., van der Aalst, W.M.P., Chesani, F., Mello, P., Storari, S.: Declarative specification and verification of service choreographies. ACM Trans. Web 4(1), 3 (2010)CrossRefGoogle Scholar
- 26.Burattin, A., Maggi, F.M., van der Aalst, W.M., Sperduti, A.: Techniques for a posteriori analysis of declarative processes. In: EDOC, Beijing, pp. 41–50. IEEE, September 2012Google Scholar
- 27.Latvala, T., Biere, A., Heljanko, K., Junttila, T.: Simple bounded LTL model checking. In: Hu, A.J., Martin, A.K. (eds.) FMCAD 2004. LNCS, vol. 3312, pp. 186–200. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30494-4_14CrossRefGoogle Scholar
- 28.Tauriainen, H.: Automata and linear temporal logic: translations with transition-based acceptance, January 2006Google Scholar
- 29.Namjoshi, K.S.: An efficiently checkable, proof-based formulation of vacuity in model checking. In: Alur, R., Peled, D.A. (eds.) CAV 2004. LNCS, vol. 3114, pp. 57–69. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-27813-9_5CrossRefGoogle Scholar
- 30.Knuth, D.E., Morris, J.H., Pratt, V.R.: Fast pattern matching in strings. SIAM J. Comput. 6, 323–350 (1977)MathSciNetCrossRefGoogle Scholar