Semi-automatic derivation of RESTful choreographies from business process choreographies

Special Section Paper
First Online:
Received:
Revised:
Accepted:

Abstract

Enterprises reach out for collaborations with other organizations in order to offer complex products and services to the market. Such collaboration and coordination between different organizations, for a good share, is facilitated by information technology. The BPMN process choreography is a modeling language for specifying the exchange of information and services between different organizations at the business level. Recently, there is a surging use of the REST architectural style for the provisioning of services on the web, but few systematic engineering approach to design their collaboration. In this paper, we address this gap in a comprehensive way by defining a semi-automatic method for the derivation of RESTful choreographies from process choreographies. The method is based on natural language analysis techniques to derive interactions from the textual information in process choreographies. The proposed method is evaluated in terms of effectiveness resulting in the intervention of a web engineer in only about 10% of all generated RESTful interactions.

Keywords

Business process choreographies RESTful choreographies Natural language analysis 
This is a preview of subscription content, log in to check access

References

  1. 1.
    OMG: Business Process Model and Notation (BPMN), Version 2.0. http://www.omg.org/spec/BPMN/2.0/ (2011)
  2. 2.
    Fielding, R.T.: Architectural styles and the design of network-based software architectures. Ph.D. thesis (2000)Google Scholar
  3. 3.
    Massé, M.: REST API Design Rulebook. O’Reilly Media Inc., Newton (2012)Google Scholar
  4. 4.
    Nikaj, A., Pittke, F., Weske, M., Mendling, J.: Semi-automatic derivation of RESTful interactions from choreography diagrams. In: Schmidt, R., Guédria, W., Bider, I., Guerreiro, S. (eds) Enterprise, Business-Process and Information Systems Modeling: Proceedings of the 17th International Conference, BPMDS 2016, 21st International Conference, EMMSAD 2016, Held at CAiSE 2016, Ljubljana, Slovenia, June 13–14, pp. 141–156. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-39429-9_10
  5. 5.
    Nikaj, A., Mandal, S., Pautasso, C., Weske, M.: From choreography diagrams to RESTful interactions. In: Norta, A., Gaaloul, W., Gangadharan, G.R., Dam, H.K. (eds) Service-Oriented Computing – ICSOC 2015 Workshops: WESOA, RMSOC, ISC, DISCO, WESE, BSCI, FORMOVES, Goa, India, Nov. 16-19, 2015, Revised Selected Papers, pp. 3–14. Springer, Berlin, Heidelberg (2016).  https://doi.org/10.1007/978-3-662-50539-7_1
  6. 6.
    Nikaj, A., Batoulis, K., Weske, M.: Rest-enabled decision making in business process choreographies. In: International Conference on Service-Oriented Computing, pp. 547–554. Springer (2016)Google Scholar
  7. 7.
    Nikaj, A., Weske, M.: Formal Specification of RESTful Choreography Properties. In: 16th International Conference on Web Engineering, ICWE 2016, Lugano, Switzerland, June 6–9, 2016. Springer (2016)Google Scholar
  8. 8.
    Pautasso, C., Wilde, E.: Push-enabling RESTful business processes. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds.) Service-Oriented Computing: Proceedings of the 9th International Conference, ICSOC 2011, Paphos, Cyprus, Dec. 5-8, pp. 32–46. Springer, Berlin, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-25535-9_3
  9. 9.
    Pautasso, C.: BPMN for REST. In: Proceedings of the 3rd International Business Process Modeling Notation Workshop (BPMN 2011), pp. 74–87 (2011)Google Scholar
  10. 10.
    Mendling, J., Reijers, H.A., Recker, J.: Activity labeling in process modeling: empirical insights and recommendations. Inf. Syst. 35(4), 467–482 (2010)CrossRefGoogle Scholar
  11. 11.
    Leopold, H., Eid-Sabbagh, R., Mendling, J., Azevedo, L.G., Baião, F.A.: Detection of naming convention violations in process models for different languages. Decis. Support Syst. 56, 310–325 (2013)CrossRefGoogle Scholar
  12. 12.
    Miller, G.A.: WordNet: a lexical database for english. Commun. ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  13. 13.
    Wu, Z., Palmer, M.: Verbs semantics and lexical selection. In: Proceedings of the 32nd Annual Meeting on Association for Computational Linguistics, pp. 133–138 (1994)Google Scholar
  14. 14.
    Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 448–453 (1995)Google Scholar
  15. 15.
    Lin, D.: An information-theoretic definition of similarity. ICML 98, 296–304 (1998)Google Scholar
  16. 16.
    Kolb, P.: Disco: a multilingual database of distributionally similar words. In: Proceedings of KONVENS-2008, Berlin (2008)Google Scholar
  17. 17.
    Kolb, P.: Experiments on the difference between semantic similarity and relatedness. In: Proceedings of the 17th Nordic Conference on Computer Linguistics (2009)Google Scholar
  18. 18.
    Reiter, E., Dale, R.: Building applied natural language generation systems. Nat. Lang. Eng. 3(1), 57–87 (1997)CrossRefGoogle Scholar
  19. 19.
    Denger, C., Berry, D.M., Kamsties, E.: Higher quality requirements specifications through natural language patterns. In: IEEE International Conference on Software—Science, Technology and Engineering, pp. 80–90 (2003)Google Scholar
  20. 20.
    Leopold, H., Mendling, J., Polyvyanyy, A.: Generating natural language texts from business process models. In: Proceedings of the 24th International Conference on Advanced Information Systems Engineering, pp. 64–79 (2012)Google Scholar
  21. 21.
    Leopold, H., Mendling, J., Polyvyanyy, A.: Supporting process model validation through natural language generation. IEEE Trans. Softw. Eng. 40(8), 818–840 (2014)CrossRefGoogle Scholar
  22. 22.
    Knöpfel, A., Gröne, B., Tabeling, P.: Fundamental modeling concepts. Effective Communication of IT Systems, Wiley, England (2005)Google Scholar
  23. 23.
    Palma, F., Gonzalez-Huerta, J., Moha, N., Guéhéneuc, Y.G., Tremblay, G.: Are restful apis well-designed? Detection of their linguistic (anti)patterns. In: Service-Oriented Computing. Lecture Notes in Computer Science. Springer (2015)Google Scholar
  24. 24.
    Valverde, F., Pastor, O.: Dealing with rest services in model-driven web engineering methods. V Jornadas Científico-Técnicas en Servicios Web y SOA, JSWEB (2009)Google Scholar
  25. 25.
    Schreier, S.: Modeling restful applications. In: Proceedings of the Second International Workshop on Restful Design, pp. 15–21. ACM (2011)Google Scholar
  26. 26.
    Laitkorpi, M., Selonen, P.: Towards a model-driven process for designing restful web services. In: IEEE International Conference on Web Services, pp. 173–180. IEEE (2009)Google Scholar
  27. 27.
    Decker, G., Kopp, O., Leymann, F., Weske, M.: Bpel4chor: extending bpel for modeling choreographies. IEEE Int. Conf. Web Serv. 2007, 296–303 (2007)Google Scholar
  28. 28.
    Jordan, D., Evdemon, J., Alves, A., Arkin, A., Askary, S., Barreto, C., Bloch, B., Curbera, F., Ford, M., Goland, Y., et al.: Web services business process execution language version 2.0. OASIS Stand. 11, 1–10 (2007)Google Scholar
  29. 29.
    Alonso, G., Casati, F., Kuno, H., Machiraju, V.: Web Services. Springer, Berlin (2004)CrossRefMATHGoogle Scholar
  30. 30.
    Mendling, J., Hafner, M.: From WS-CDL choreography to BPEL process orchestration. J. Enterp. Inf. Manag. (JEIM) 21, 506–515 (2008)Google Scholar
  31. 31.
    Kavantzas, N.: Web services choreography description language (ws-cdf) version 1.0. http://www.w3.org/TR/ws-cdl-10/ (2004)
  32. 32.
    Ouyang, C., Dumas, M., Van Der Aalst, W.M.P., Ter Hofstede, A.H.M., Mendling, J.: From business process models to process-oriented software systems. ACM Trans. Softw. Eng. Methodol. 19(1), 2–37 (2009)CrossRefGoogle Scholar
  33. 33.
    Ziemann, J., Mendling, J.: EPC-based modelling of BPEL processes: a pragmatic transformation approach. In: International Conference on Modern Information Technology in the Innovation Processes of the Industrial Enterprises, Genova, Italy (2005)Google Scholar
  34. 34.
    Mendling, J., Lassen, K.B., Zdun, U.: On the transformation of control flow between block-oriented and graph-oriented process modelling languages. IJBPIM 3(2), 96–108 (2008)CrossRefGoogle Scholar
  35. 35.
    Weber, I., Xu, X., Riveret, R., Governatori, G., Ponomarev, A., Mendling, J.: Untrusted business process monitoring and execution using blockchain. In: La Rosa, M., Loos, P., Pastor, O. (eds.) Business Process Management: Proceedings of the 14th International Conference, BPM 2016, Rio de Janeiro, Brazil, Sept. 18–22, pp. 329–347. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-45348-4_19
  36. 36.
    Omohundro, S.: Cryptocurrencies, smart contracts, and artificial intelligence. AI Matters 1(2), 19–21 (2014)MathSciNetCrossRefGoogle Scholar
  37. 37.
    Navigli, R., Ponzetto, S.P.: Babelnet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artif. Intell. 193, 217–250 (2012)Google Scholar
  38. 38.
    Medina-Mora, R., Winograd, T., Flores, R., Flores, F.: The action workflow approach to workflow management technology. In: Proceedings of the 1992 ACM conference on Computer-supported cooperative work, pp. 281–288. ACM (1992)Google Scholar
  39. 39.
    Cohen, W.W., Carvalho, V.R., Mitchell, T.M.: Learning to classify email into "speech acts". EMNLP 4, 309–316 (2004)Google Scholar
  40. 40.
    Pittke, F., Leopold, H., Mendling, J.: Automatic detection and resolution of lexical ambiguity in process models. IEEE Trans. Softw. Eng. 41(6), 526–544 (2015)CrossRefGoogle Scholar
  41. 41.
    Weidlich, M., Mendling, J., Weske, M.: Efficient consistency measurement based on behavioral profiles of process models. IEEE Trans. Softw. Eng. 37(3), 410–429 (2011)CrossRefGoogle Scholar
  42. 42.
    Leopold, H., Niepert, M., Weidlich, M., Mendling, J., Dijkman, R., Stuckenschmidt, H.: Probabilistic optimization of semantic process model matching. Bus. Process Manag. 7481, 319–334 (2012)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Hasso Plattner Institute, University of PotsdamPotsdamGermany
  2. 2.Institute for Information BusinessWU ViennaViennaAustria

Personalised recommendations