Abstract
Business Process Modeling Notation (BPMN) is a technique for graphically drawing and illustrating business processes in diagramtic form. Semantic of Business Vocabulary and Business Rules (SBVR) is a declarative language used to define business vocabulary, rules and policy. Several times inconsistencies occur between BPMN and SBVR as they are independently maintained. Our aim is to investigate techniques for automatically detecting inconsistencies between business process and rules. We present a method for inconsistency detection (between BPMN and SBVR) based on converting SBVR rules to graphical representation and apply sub graph-isomorphism to detect instances of inconsistencies between BPMN and SBVR models. We propose a multi-step process framework for identification of instances of inconsistencies between the two models. We first generate an XML of BPMN diagram and apply parsing and tag extraction. We then apply Stanford NLP Parser to generate parse tree of rules. The detailed information about the parse tree is stored in the form of Typed Dependency which represent grammatical relation between words of a sentence. We utilize the grammatical relation extract triplet (actor-action-object) of a sentence. We find node-induced sub-graph of all possible length of nodes of a graph and apply VF2 Algorithm to detect instances of inconsistency between sub graphs. Finally, we evaluate the proposed research framework by conducting experiments on synthetic dataset to validate the accuracy and effectiveness of our approach.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cordella, L.P., Foggia, P., Sansone, C., Vento, M.: An improved algorithm for matching large graphs. In: 3rd IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition, Cuen, pp. 149–159 (2001)
Cordella, L., Foggia, P., Sansone, C., Vento, M.: A (sub)graph isomorphism algorithm for matching large graphs. Pattern Anal. Mach. Intell. IEEE Trans. 26(10), 1367–1372 (2004)
Cordella, L.P., Foggia, P., Sansone, C., Vento, M.: Subgraph transformations for the inexact matching of attributed relational graphs. Springer, Heidelberg (1998)
Cordella, L.P., Foggia, P., Sansone, C., Vento, M.: Performance evaluation of the vf graph matching algorithm. In: Proceedings of the International Conference on Image Analysis and Processing, 1999, pp. 1172–1177. IEEE (1999)
Dali, L., Fortuna, B.: Triplet extraction from sentences using svm. In: Proceedings of SiKDD (2008)
Habich, D., Richly, S., Demuth, B., Gietl, F., Spilke, J., Lehner, W., Assmann, U.: Joining business rules and business processes. In: Proceedings of IT (2010)
Krogstie, J., McBrien, P., Owens, R., Seltveit, A.H.: Information systems development using a combination of process and rule based approaches. In: Andersen, R., Bubenko, J.A., Solvberg, A. (eds.) Advanced Information Systems Engineering. LNCS, vol. 498, pp. 319–335. Springer, Heidelberg (1991)
Mickeviciute, E., Nemuraite, L., Butleris, R.: Applying SBVR business vocabulary and business rules for creating BPMN process models. In: Abramowicz, W., Kokkinaki, A. (eds.) BIS 2014 Workshops. LNBIP, vol. 183, pp. 105–116. Springer, Heidelberg (2014)
Myint, Z.T.T., Win, K.K.: Triple patterns extraction for accessing data on ontology. Int. J. Future Comput. Commun. 3(1), 40 (2014)
Rusu, D., Dali, L., Fortuna, B., Grobelnik, M., Mladenic, D.: Triplet extraction from sentences. In: Proceedings of the 10th International Multiconference Information Society-IS, pp. 8–12 (2007)
Sharma, D.K., Prakash, N., Sharma, H., Singh, D.: Automatic construction of process template from business rule. In: 2014 Seventh International Conference on Contemporary Computing (IC3), pp. 419–424. IEEE (2014)
Skersys, T., Kapocius, K., Butleris, R., Danikauskas, T.: Extracting business vocabularies from business process models: Sbvr and bpnm standards-based approach. Comput. Sci. Inf. Syst. 11(4), 1515–1535 (2014)
Skersys, T., Tutkute, L., Butleris, R., Butkiene, R.: Extending bpmn business process model with sbvr business vocabulary and rules. Inf. Technol. Control 41(4), 356–367 (2012)
Steen, B., Pires, L.F., Iacob, M.E.: Automatic generation of optimal business processes from business rules. In: 2010 14th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW), pp. 117–126. IEEE (2010)
Ullmann, J.R.: An algorithm for subgraph isomorphism. J. ACM 23, 31–42 (1976)
Zur Muehlen, M., Indulska, M., Kittel, K.: Towards integrated modeling of business processes and business rules. In: ACIS 2008 Proceedings, p. 108 (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Mishra, A., Sureka, A. (2015). A Graph Processing Based Approach for Automatic Detection of Semantic Inconsistency Between BPMN Process Model and SBVR Rules. In: Prasath, R., Vuppala, A., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2015. Lecture Notes in Computer Science(), vol 9468. Springer, Cham. https://doi.org/10.1007/978-3-319-26832-3_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-26832-3_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26831-6
Online ISBN: 978-3-319-26832-3
eBook Packages: Computer ScienceComputer Science (R0)