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Re-learning of Business Process Models from Legacy System Using Incremental Process Mining

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Enterprise Information Systems (ICEIS 2013)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 190))

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Abstract

Several approaches have already been proposed to extract both business processes and business rules from a legacy source code. These approaches usually consider static and dynamic source code analysis for re-learning of these models. However, business processes have components that cannot be directly extracted by static analysis (i.e., process participants and concurrent tasks). Moreover, most of well-known process mining algorithms used in dynamic analysis do not support all required operations of incremental extraction. Re-learning of large legacy systems can benefit from an incremental analysis strategy in order to provide iterative extraction of process models. This paper discusses an approach for business knowledge extraction from legacy systems through incremental process mining. Discovery results can be used in various ways by business analysts and software architects, e.g. documentation of legacy systems or for re-engineering purposes.

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Authors and Affiliations

  1. Department of Informatics, Federal University of Rio Grande do Sul, UFRGS, Porto Alegre, Brazil

    André Cristiano Kalsing, Cirano Iochpe, Lucinéia Heloisa Thom & Gleison Samuel do Nascimento

Authors
  1. André Cristiano Kalsing
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  2. Cirano Iochpe
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  3. Lucinéia Heloisa Thom
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  4. Gleison Samuel do Nascimento
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Corresponding author

Correspondence to André Cristiano Kalsing .

Editor information

Editors and Affiliations

  1. Groupe ESEO, Angers, France

    Slimane Hammoudi

  2. Polytechnic Institute of Setúbal, Setúbal, Portugal & INSTICC, Setúbal, Portugal

    José Cordeiro

  3. Wroclaw University of Economics, Wroclaw, Poland & Macquarie University, Sydney, NSW, Australia

    Leszek A. Maciaszek

  4. Polytechnic Institute of Setúbal, Setúbal, Portugal & INSTICC, Setúbal, Poland

    Joaquim Filipe

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Kalsing, A.C., Iochpe, C., Thom, L.H., do Nascimento, G.S. (2014). Re-learning of Business Process Models from Legacy System Using Incremental Process Mining. In: Hammoudi, S., Cordeiro, J., Maciaszek, L., Filipe, J. (eds) Enterprise Information Systems. ICEIS 2013. Lecture Notes in Business Information Processing, vol 190. Springer, Cham. https://doi.org/10.1007/978-3-319-09492-2_19

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  • DOI: https://doi.org/10.1007/978-3-319-09492-2_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09491-5

  • Online ISBN: 978-3-319-09492-2

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