Aspect Mining in Business Process Management

  • Amin Jalali
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 194)

Abstract

Automatic discovery of process models from event logs is an important and promising area in Business Process Management. Process models document how business processes should be performed, so they capture different concerns related to business processes. Some of these concerns are not limited to one process model, and they are repeated in many others as well, called cross-cutting concerns. Although many works have been done to enable discovering different process models, there is no investigation about how models with cross-cutting concerns can be discovered from even logs. Therefore, this work proposes an approach to enable discovering these models from event logs. The investigation is performed based on a case-study from the banking domain. The result shows how these concerns hinder existing process discovery techniques, and how the proposed approach can solve the problem.

Keywords

Process Mining Aspect Mining Process Discovery Business Process Management Aspect Oriented 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    van der Aalst, W.M.P.: Process cubes: Slicing, dicing, rolling up and drilling down event data for process mining. In: Song, M., Wynn, M.T., Liu, J. (eds.) AP-BPM 2013. LNBIP, vol. 159, pp. 1–22. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  2. 2.
    van der Aalst, W., et al.: Process mining manifesto. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM Workshops 2011, Part I. LNBIP, vol. 99, pp. 169–194. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    van der Aalst, W.M.P., Weijters, A.J.M.M.: Process mining: a research agenda. Computers in Industry 53(3), 231–244 (2004)CrossRefGoogle Scholar
  4. 4.
    van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128–1142 (2004)CrossRefGoogle Scholar
  5. 5.
    Beheshti, S.M.R.: Organizing, Querying, and Analyzing Ad-hoc Processes Data. PhD thesis, University of New South Wales Sydney, Australia (2012)Google Scholar
  6. 6.
    Beheshti, S.-M.-R., Benatallah, B., Motahari-Nezhad, H.R.: Enabling the analysis of cross-cutting aspects in ad-hoc processes. In: Salinesi, C., Norrie, M.C., Pastor, Ó. (eds.) CAiSE 2013. LNCS, vol. 7908, pp. 51–67. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  7. 7.
    Breu, S.: Extending dynamic aspect mining with static information. In: Fifth IEEE International Workshop on Source Code Analysis and Manipulation 2005, pp. 57–65 (2005)Google Scholar
  8. 8.
    Breu, S., Krinke, J.: Aspect mining using event traces. In: Proceedings of the 19th International Conference on Automated Software Engineering 2004, pp. 310–315 (September 2004)Google Scholar
  9. 9.
    Breu, S., Krinke, J.: Aspect mining using event traces. In: Proceedings of the 19th International Conference on Automated Software Engineering 2004, pp. 310–315. IEEE (2004)Google Scholar
  10. 10.
    Breu, S.: Th. Zimmermann. Mining aspects from version history. In: 21st IEEE/ACM International Conference on Automated Software Engineering, ASE 2006, pp. 221–230. IEEE (2006)Google Scholar
  11. 11.
    Cappelli, C., Santoro, F.M., do Prado Leite, J.C.S., Batista, T., Medeiros, A.L., Romeiro, C.S.C.: Reflections on the modularity of business process models: The case for introducing the aspect-oriented paradigm. BPM Journal 16, 662–687 (2010)Google Scholar
  12. 12.
    Ceccato, M., Marin, M., Mens, K., Moonen, L., Tonella, P., Tourwe, T.: A qualitative comparison of three aspect mining techniques. In: Proceedings of the 13th International Workshop on Program Comprehension, IWPC 2005, pp. 13–22. IEEE (2005)Google Scholar
  13. 13.
    Ceccato, M., Marin, M., Mens, K., Moonen, L., Tonella, P., Tourwé, T.: Applying and combining three different aspect mining techniques. Software Quality Journal 14(3), 209–231 (2006)CrossRefGoogle Scholar
  14. 14.
    Ceccato, M., Marin, M., Mens, K., Moonen, L., Tonella, P., Tourwé, T.: Applying and combining three different aspect mining techniques. Software Quality Journal 14(3), 209–231 (2006)CrossRefGoogle Scholar
  15. 15.
    Charfi, A., Müller, H., Mezini, M.: Aspect-Oriented Business Process Modeling with AO4BPMN. In: Kühne, T., Selic, B., Gervais, M.-P., Terrier, F. (eds.) ECMFA 2010. LNCS, vol. 6138, pp. 48–61. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  16. 16.
    Di Francescomarino, C., Tonella, P.: Crosscutting concern mining in business processes. IET Software 5(6), 552–562 (2011)CrossRefGoogle Scholar
  17. 17.
    van Dongen, B.F., de Medeiros, A.K.A., Verbeek, H.M.W(E.), Weijters, A.J.M.M.T., van der Aalst, W.M.P.: The prom framework: A new era in process mining tool support. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 444–454. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  18. 18.
    Günther, C.W., van der Aalst, W.M.P.: Fuzzy mining – adaptive process simplification based on multi-perspective metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328–343. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  19. 19.
    Gybels, K., Kellens, A.: An experiment in using inductive logic programming to uncover pointcuts. In: First European Interactive Workshop on Aspects in Software (2004)Google Scholar
  20. 20.
    He, L., Bai, H.: Aspect mining using clustering and association rule method. International Journal of Computer Science and Network Security 6(2A), 247–251 (2006)Google Scholar
  21. 21.
    Herbst, J., Karagiannis, D.: Workflow mining with inwolve. Computers in Industry 53(3), 245–264 (2004); Process / Workflow MiningGoogle Scholar
  22. 22.
    Jalali, A., Wohed, P., Ouyang, C.: Aspect oriented business process modelling with precedence. In: Mendling, J., Weidlich, M. (eds.) BPMN 2012. LNBIP, vol. 125, pp. 23–37. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  23. 23.
    Jalali, A., Wohed, P., Ouyang, C., Johannesson, P.: Dynamic weaving in aspect oriented business process management. In: Meersman, R., Panetto, H., Dillon, T., Eder, J., Bellahsene, Z., Ritter, N., De Leenheer, P., Dou, D. (eds.) ODBASE 2013. LNCS, vol. 8185, pp. 2–20. Springer, Heidelberg (2013)Google Scholar
  24. 24.
    Li, J., Liu, D., Yang, B.: Process mining: Extending α-algorithm to mine duplicate tasks in process logs. In: Chang, K.C.-C., Wang, W., Chen, L., Ellis, C.A., Hsu, C.-H., Tsoi, A.C., Wang, H. (eds.) APWeb/WAIM 2007. LNCS, vol. 4537, pp. 396–407. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  25. 25.
    de Medeiros, A.K.A., van der Aalst, W.M.P., Weijters, A.J.M.M.T.: Workflow mining: Current status and future directions. In: Meersman, R., Schmidt, D.C. (eds.) CoopIS/DOA/ODBASE 2003. LNCS, vol. 2888, pp. 389–406. Springer, Heidelberg (2003)Google Scholar
  26. 26.
    de Medeiros, A.K.A.: Genetic process mining. PhD thesis, Technische Universiteit Eindhoven (2006)Google Scholar
  27. 27.
    Gu, C.Q., Chang, H.Y., Yi, Y.: Workflow mining: Extending the α-algorithm to mine duplicate tasks. In: 2008 International Conference on Machine Learning and Cybernetics, vol. 1, pp. 361–368 (2008)Google Scholar
  28. 28.
    Shepherd, D., Pollock, L., Tourwé, T.: Using language clues to discover crosscutting concerns. ACM SIGSOFT Software Engineering Notes 30, 1–6 (2005)CrossRefGoogle Scholar
  29. 29.
    Tonella, P., Ceccato, M.: Aspect mining through the formal concept analysis of execution traces. In: Proceedings of the 11th Working Conference on Reverse Engineering 2004, pp. 112–121 (November 2004)Google Scholar
  30. 30.
    Tonella, P., Ceccato, M.: Aspect mining through the formal concept analysis of execution traces. In: Proceedings of the 11th Working Conference on Reverse Engineering 2004, pp. 112–121. IEEE (2004)Google Scholar
  31. 31.
    Tourwe, T., Mens, K.: Mining aspectual views using formal concept analysis. In: Fourth IEEE International Workshop on Source Code Analysis and Manipulation 2004, pp. 97–106. IEEE (2004)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Amin Jalali
    • 1
  1. 1.Department of Computer and Systems SciencesStockholm UniversitySweden

Personalised recommendations