Skip to main content

Process Mining Framework for Software Processes

  • Conference paper
Software Process Dynamics and Agility (ICSP 2007)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4470))

Included in the following conference series:

Abstract

Software development processes are often not explicitly modelled and sometimes even chaotic. In order to keep track of the involved documents and files, engineers use Software Configuration Management (SCM) systems. Along the way, those systems collect and store information on the software process itself. Thus, SCM information can be used for constructing explicit process models, which is called software process mining. In this paper we show that (1) a Process Mining Framework can be used for obtaining software process models as well as for analysing and optimising them; (2) an algorithmic approach, which arose from our research on software processes, is integrated in the framework.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. van Dongen, B., et al.: 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)

    Google Scholar 

  2. MSR 2005 International Workshop on Mining Software Repositories. In: ICSE ’05: Proceedings of the 27th international conference on Software engineering, ACM Press, New York (2005)

    Google Scholar 

  3. Sandusky, R.J., Gasser, L., Ripoche, G.: Bug Report Networks: Varieties, Strategies, and Impacts in a F/OSS Development Community. In: MSR 2004: International Workshop on Mining Software Repositories (2004), citeseer.ist.psu.edu/sandusky04bug.html

  4. Iannacci, F.: Coordination Processes in Open Source Software Development: The Linux Case Study (Apr. 2005), http://opensource.mit.edu/papers/iannacci3.pdf

  5. Agrawal, R., Srikant, R.: Mining sequential patterns. In: Yu, P.S., Chen, A.S.P. (eds.) Eleventh International Conference on Data Engineering, Taipei, Taiwan, pp. 3–14. IEEE Computer Society Press, Los Alamitos (1995), citeseer.ist.psu.edu/agrawal95mining.html

    Chapter  Google Scholar 

  6. van der Aalst, W., et al.: Workflow Mining: A Survey of Issues and Approaches. Data and Knowledge Engineering 47(2), 237–267 (2003)

    Article  Google Scholar 

  7. Agrawal, R., Gunopulos, D., Leymann, F.: Mining Process Models from Workflow Logs. In: Schek, H.-J., et al. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 469–483. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  8. Cook, J.E., Wolf, A.L.: Discovering Models of Software Processes from Event-Based Data. ACM Transactions on Software Engineering and Methodology 7(3), 215–249 (1998)

    Article  Google Scholar 

  9. Cook, J.E., et al.: Discovering models of behavior for concurrent workflows. Computers in Industry 53(3), 297–319 (2004)

    Article  Google Scholar 

  10. Kindler, E., Rubin, V., Schäfer, W.: Incremental Workflow mining based on Document Versioning Information. In: Li, M., Boehm, B., Osterweil, L.J. (eds.) SPW 2005. LNCS, vol. 3840, pp. 287–301. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Kindler, E., Rubin, V., Schäfer, W.: Activity mining for discovering software process models. In: Biel, B., Book, M., Gruhn, V. (eds.) Proc. of the Software Engineering 2006 Conference, Leipzig, Germany, March 2006. LNI, vol. P-79, pp. 175–180. Gesellschaft für Informatik (2006)

    Google Scholar 

  12. van der Aalst, W., et al.: Process Mining: A Two-Step Approach using Transition Systems and Regions. BPM Center Report BPM-06-30, BPM Center, BPMcenter.org (Dec. 2006)

    Google Scholar 

  13. Cortadella, J., et al.: Deriving Petri nets from finite transition systems. IEEE Transactions on Computers 47(8), 859–882 (1998), citeseer.ist.psu.edu/article/cortadella98deriving.html

    Article  MathSciNet  Google Scholar 

  14. Kindler, E., Rubin, V.: Process Mining and Petri Net Synthesis. In: Eder, J., Dustdar, S. (eds.) Business Process Management Workshops. LNCS, vol. 4103, Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  15. Cortadella, J., et al.: Petrify: a tool for manipulating concurrent specifications and synthesis of asynchronous controllers. IEICE Transactions on Information and Systems E80-D(3), 315–325 (1997), citeseer.ist.psu.edu/cortadella96petrify.html

    Google Scholar 

  16. van der Aalst, W., Weijters, A., Maruster, L.: Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128–1142 (2004)

    Article  Google Scholar 

  17. van Dongen, B., van der Aalst, W.: Multi-Phase Process Mining: Building Instance Graphs. In: Atzeni, P., et al. (eds.) ER 2004. LNCS, vol. 3288, pp. 362–376. Springer, Heidelberg (2004)

    Google Scholar 

  18. Weijters, A., van der Aalst, W.: Rediscovering Workflow Models from Event-Based Data using Little Thumb. Integrated Computer-Aided Engineering 10(2), 151–162 (2003)

    Google Scholar 

  19. van der Aalst, W., Medeiros, A., Weijters, A.: Genetic Process Mining. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 48–69. Springer, Heidelberg (2005)

    Google Scholar 

  20. van der Aalst, W., Reijers, H., Song, M.: Discovering Social Networks from Event Logs. Computer Supported Cooperative work 14(6), 549–593 (2005)

    Article  Google Scholar 

  21. Günther, C., van der Aalst, W.: Mining Activity Clusters from Low-level Event Logs. BETA Working Paper Series, WP 165, Eindhoven University of Technology, Eindhoven (2006)

    Google Scholar 

  22. Rozinat, A., van der Aalst, W.: Conformance Testing: Measuring the Fit and Appropriateness of Event Logs and Process Models. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 163–176. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  23. van der Aalst, W., Beer, H., Dongen, B.: Process Mining and Verification of Properties: An Approach based on Temporal Logic. BETA Working Paper Series, WP 136, Eindhoven University of Technology, Eindhoven (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Qing Wang Dietmar Pfahl David M. Raffo

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Rubin, V., Günther, C.W., van der Aalst, W.M.P., Kindler, E., van Dongen, B.F., Schäfer, W. (2007). Process Mining Framework for Software Processes. In: Wang, Q., Pfahl, D., Raffo, D.M. (eds) Software Process Dynamics and Agility. ICSP 2007. Lecture Notes in Computer Science, vol 4470. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72426-1_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-72426-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72425-4

  • Online ISBN: 978-3-540-72426-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics