Extracting and Conserving Production Data as Test Cases in Executable Business Process Architectures

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Lübke, D.: Extracting and Conserving Production Data as Test Cases in Executable Business Process Architectures. In: Cruz-Cunha, M.M.; Quintela Varajão, J.E.; Rijo, R.; Martinho, R.; Peppard, J.; San Cristóbal, J.R.; Monguet, J. (Eds.): CENTERIS 2017 - International Conference on ENTERprise Information Systems : ProjMAN 2017 - International Conference on Project MANagement : HCist 2017 - International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2017. Amsterdam [u.a.] : Elsevier, 2017 (Procedia computer science ; 121), S. 1006-1013. DOI: https://doi.org/10.1016/j.procs.2017.11.130

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/3335

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Sum total of downloads: 146




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Abstract: 
Because executable business processes are an important and critical software asset of organizations because they control and integrate critical information systems. Thus, testing them thoroughly is a very important task within the software development process. However, failures due to implementation defects still occur in production, which in turn means that the development team needs to analyze, fix and repair the failing processes. In order to support the activities of reproducing the problem outside of the production system and to create better test cases for verifying the fixed implementation, we propose to use process mining techniques on the production process event logs to aid the support & development teams. With our approach it is possible to automatically extract a working unit test case with all partner services being mocked that can run in a development environment. Within in this paper we present the extraction algorithm, our implementation, and possible ways to integrate the tool into the support & development process. © 2017 The Authors. Published by Elsevier B.V.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: BookPart
Publishing status: publishedVersion
Issue Date: 2017
Appears in Collections:Fakultät für Elektrotechnik und Informatik

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pos. country downloads
total perc.
1 image of flag of Germany Germany 85 58.22%
2 image of flag of United States United States 21 14.38%
3 image of flag of China China 12 8.22%
4 image of flag of Ecuador Ecuador 7 4.79%
5 image of flag of Russian Federation Russian Federation 2 1.37%
6 image of flag of Indonesia Indonesia 2 1.37%
7 image of flag of Czech Republic Czech Republic 2 1.37%
8 image of flag of Switzerland Switzerland 2 1.37%
9 image of flag of Brazil Brazil 2 1.37%
10 image of flag of Saudi Arabia Saudi Arabia 1 0.68%
    other countries 10 6.85%

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