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Mining change operations for workflow platform as a service

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Abstract

Workflow platform as a service (WaaS) allows users to define, integrate and run workflow based applications and it is becoming popular with the rapid development of cloud computing. However, for a workflow-enabled application, a single workflow model is not possible to meet various requirements from different users. Therefore, many workflow platforms provide tools that can be used to change the workflow model by users. An approach to mine users’ workflow change operations is proposed, through which change rules can be discovered and be reused to configure the workflow model automatically in the future. The method to retrieve the change operations is firstly introduced and a change rule-mining algorithm is given. Then the process of applying change rules to configure the workflow model is described. Finally, a prototype system and a case study are presented.

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References

  1. Accorsi, R., Stocker, T., Müller, G.: On the Exploitation of Process Mining for Security Audits: the Process Discovery Case, pp. 1462–1468. Proceedings of the 28th Annual ACM Symposium on Applied Computing, SAC’13, Coimbra, Portugal (2013). doi:10.1145/2245276.2232051

  2. Adriansyah, A., Buijs, J.C.A.M.: Mining process performance from event logs. Lect. Notes Bus. Inf. Process. 132, 217–218 (2013)

    Article  Google Scholar 

  3. Amazon, Amazon Simple Workflow Service, http://aws.amazon.com/swf/ (2012) Accessed 28 Oct. 2013

  4. Bille, P.A.: Survey on tree edit distance and related problems. Theor. Comput. Sci. 337(1–3), 217–239 (2005). doi:10.1016/j.tcs.2004.12.030

    Article  MATH  MathSciNet  Google Scholar 

  5. Bose, R.P.J.C., van der Aalst, W.M.P.: Process diagnostics using trace alignment: opportunities, issues, and challenges. Inf. Syst. 37(2), 117–141 (2012)

    Article  Google Scholar 

  6. Di Ciccio, C., Mecella, M.: A Two-step Fast Algorithm for the Automated Discovery of Declarative Workflows, Computational Intelligence and Data Mining (CIDM), 2013 I.E. Symposium on, 16–19 April, 2013: 135–142 (2013). doi:10.1109/CIDM.2013.6597228

  7. Fabrizio, B., Yefim, V. N.,Massimo, P.: Market Trends: Platform as a Service,Worldwide, 2012–2016, http://www.gartner.com/id=2188816 (2012) Accessed 28 Oct. 2013

  8. Gil, Y., Deelman, E., Blythe, J., et al.: Artificial intelligence and grids: workflow planning and beyond. IEEE Intell. Syst. 19(1), 26–33 (2004). doi:10.1109/MIS.2004.1265882

    Article  Google Scholar 

  9. Gottschalk, F., van der Aalst, W.M.P., Jansen-Vullers, M.H., et al.: Configurable workflow models. Int. J. Coop. Inf. Syst. 17(2), 177–211 (2008). doi:10.1142/S0218843008001798

    Article  Google Scholar 

  10. Günther, C.W., Rinderle, S.B., Reichert, M., et al.: Using process mining to learn from process changes in evolutionary systems. Int. J. Bus. Process Integr. Manag. Spec. Issue Bus. Process Flex. 3(1), 61–78 (2008). doi:10.1504/IJBPIM.2008.019348

    Article  Google Scholar 

  11. Jian, C., Haiyan, Z., Jie, W., et al.: Verifying dynamic workflow change based on executable path. Int. J. Intell. Control Syst. 12(1), 37–44 (2007)

    Google Scholar 

  12. Küster, J.M., Gerth, C., Förster, A., et al.: Detecting and resolving process model differences in the absence of a change Log. Lect. Notes Comput. Sci 5240, 244–260 (2008)

    Article  Google Scholar 

  13. Küster, J.M., Gerth, C., Förster, A., et al.: Detecting and resolving process differences in the absence of a change Log. Lect. Notes Comput. Sci 5240, 244–260 (2008). doi:10.1007/978-3-540-85758-7_19

    Article  Google Scholar 

  14. Küster, J.M., Gerth, C., Engels, G.: Dependent and conflicting change operations of process models. Lect. Notes Comput. Sci 5562, 158–173 (2009). doi:10.1007/978-3-642-02674- 4_12

    Article  Google Scholar 

  15. Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs: a constructive approach. Lect. Notes Comput. Sci. (7927), 311–329 (2013). doi:10.1109/CIDM.2013.6597228

  16. Leymann, F., Roller, D.: Production workflow: Concepts and Techniques, Prentice-Hall. (2000)

  17. Li, C., Reichert, M., Wombacher, A.: Mining Process Variants: Goals and Issues. Proceedings of the 5th International Conference on Services Computing (SCC), 7–11 July 2008, Los Alamitos, CA: 573–576 (2008). doi:10.1109/SCC.2008.103

  18. Li, C., Reichert, M., Wombacher, A.: On measuring process model similarity based on high-level change operations. Lect. Notes Comput. Sci 5231, 248–264 (2008). doi:10.1007/978-3-540-87877-3_19

    Article  Google Scholar 

  19. Li, C., Reichert, M., Wombacher, A.: Discovering reference models by mining process variants using a heuristic approach. Lect. Notes Comput. Sci 5701, 344–362 (2009). doi:10.1007/978-3-642-03848-8_23

    Article  Google Scholar 

  20. Minor, M., Tartakovski, A., Schmalen, D.: Agile workflow technology and case-based change reuse for long-term processes. Int. J. Intell. Inf. Technol. 4(1), 80–98 (2008). doi:10.4018/jiit.2008010104

    Article  Google Scholar 

  21. Ouangraoua, A., Ferraro, P.A.: Constrained edit distance algorithm between semi-ordered trees. Theor. Comput. Sci. 410(8–10), 837–846 (2009). doi:10.1016/j.tcs.2008.11.022

    Article  MATH  MathSciNet  Google Scholar 

  22. Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo (1993)

    Google Scholar 

  23. Rinderle, S., Reichert, M., Dadam, P.: Disjoint and overlapping process changes: challenges, solutions, applications. Lect. Notes Comput. Sci 3290, 101–120 (2004). doi:10.1007/978-3-540-30468-5_9

    Article  Google Scholar 

  24. Saleforce: Introducing the new Force.com Visual Process Manager, http://www.salesforce.com/platform/process/ (2013) Accessed 28 Oct. 2013

  25. Scheidegger, C.E., Vo, H.T., Koop, D., et al.: Querying and re-using workflows with VisTrails. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data (SIGMOD’08), pp. 1251–1254. ACM, New York (2008)

  26. Tao, J., Jianmin, W., Lijie, W.: Efficient retrieval of similar business process models based on structure. Lect. Notes Comput. Sci 7044, 56–63 (2011)

    Article  Google Scholar 

  27. Valiente, G.: Algorithms on Trees and Graphs. Springer, Berlin (2002)

    Book  MATH  Google Scholar 

  28. van der Aalst, W.M.P., Jablonski, S.: Dealing with workflow change: identification of issues and solutions. Int. J.Comput. Syst. Sci. Eng. 15(5), 267–276 (2000)

    Google Scholar 

  29. van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes, 1st edn. Springer Publishing Company, Incorporated (2011)

  30. van der Aalst, W.M.P., Weijters, A., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004). doi:10.1109/TKDE.2004.47

    Article  Google Scholar 

  31. Vanhatalo, J., Völzer, H., Leymann, F., et al.: Automatic workflow graph refactoring and completion. Lect. Notes Comput. Sci 5364, 100–115 (2008). doi:10.1007/978-3-540-89652-4_11

    Article  Google Scholar 

  32. Vanhatalo, J., Völzer, H., Koehler, J.: The refined process structure tree. Data Knowl. Eng. 68(9), 793–818 (2009). doi:10.1007/978-3-540-85758- 7_10

    Article  Google Scholar 

  33. WfMC: Glossary, Terminology and Glossary, 3rd Edition. Document No WFMC-TC-1011. Workflow Management Coalition. Winchester (1999)

  34. William, Y. C., Hosame, AA, Jessica F. S.: Transforming Enterprise Cloud Services, Springer (2010)

  35. Zhiqiang, Y., Dijkman, R.M., Grefen, P.W.P.J.: Business process model repositories - framework and survey. Inf. Softw. Technol. 54(4), 380–395 (2012). doi:10.1016/j.infsof.2011.11.005

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800# Dong-Chuan Road, Shanghai, 200240, China

    Jian Cao, Yan Yao & Yi Wang

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  1. Jian Cao
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  2. Yan Yao
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  3. Yi Wang
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Correspondence to Jian Cao.

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Cao, J., Yao, Y. & Wang, Y. Mining change operations for workflow platform as a service. World Wide Web 18, 1071–1092 (2015). https://doi.org/10.1007/s11280-014-0308-y

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  • DOI: https://doi.org/10.1007/s11280-014-0308-y

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