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Incremental Workflow Mining Based on Document Versioning Information

  • Conference paper
Unifying the Software Process Spectrum (SPW 2005)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 3840))

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Abstract

Current enterprises spend much effort to obtain precise models of their system engineering processes in order to improve the process capability of the organization. The manual design of workflow models is complicated, time-consuming and error-prone; capabilities of human beings in detecting discrepancies between the actual process and the process model are rather limited. Therefore, automatic techniques for deriving these models are becoming more and more important.

In this paper, we present an idea that exploits the user interaction with a version management system for the incremental automatic derivation, refinement and analysis of process models. Though this idea is not fully worked out yet, we sketch the architecture of the solution and the algorithms for the main steps of incremental automatic derivation of process models.

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Author information

Authors and Affiliations

  1. Software Engineering Group, University of Paderborn, Warburger Str. 100, D-33098, Paderborn, Germany

    Ekkart Kindler, Vladimir Rubin & Wilhelm Schäfer

Authors
  1. Ekkart Kindler
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  2. Vladimir Rubin
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  3. Wilhelm Schäfer
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Editor information

Editors and Affiliations

  1. State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, 100080, Beijing, China

    Mingshu Li

  2. CS, University of Southern California, Los Angeles, California, USA

    Barry Boehm

  3. Laboratory for Advanced Software Engineering Research (LASER), University of Massachusetts at Amherst, 01003, Amherst, MA

    Leon J. Osterweil

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© 2006 Springer-Verlag Berlin Heidelberg

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Kindler, E., Rubin, V., Schäfer, W. (2006). Incremental Workflow Mining Based on Document Versioning Information. In: Li, M., Boehm, B., Osterweil, L.J. (eds) Unifying the Software Process Spectrum. SPW 2005. Lecture Notes in Computer Science, vol 3840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11608035_25

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  • DOI: https://doi.org/10.1007/11608035_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31112-6

  • Online ISBN: 978-3-540-32450-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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