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2018 | OriginalPaper | Buchkapitel

A Machine Learning Based Approach to Application Landscape Documentation

verfasst von : Jörg Landthaler, Ömer Uludağ, Gloria Bondel, Ahmed Elnaggar, Saasha Nair, Florian Matthes

Erschienen in: The Practice of Enterprise Modeling

Verlag: Springer International Publishing

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Abstract

In the era of digitalization, IT landscapes keep growing along with complexity and dependencies. This amplifies the need to determine the current elements of an IT landscape for the management and planning of IT landscapes as well as for failure analysis. The field of enterprise architecture documentation sought for more than a decade for solutions to minimize the manual effort to build enterprise architecture models or automation. We summarize the approaches presented in the last decade in a literature survey. Moreover, we present a novel, machine-learning based approach to detect and to identify applications in an IT landscape.

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Vorheriges Kapitel Grass-Root Enterprise Modeling: Issues and Potentials of Retrieving Models from Powerpoint

Nächstes Kapitel Case and Activity Identification for Mining Process Models from Middleware

Flexera FlexNet, https://www.flexera.com, last accessed in November 2017.

Note that Holm et al. [10] is an extension of Buschle et al. [3].

In most papers, the authors use an earlier version of the ArchiMate framework, e.g. ArchiMate 2.0. To allow comparability, the EA entities of earlier version versions have been carefully mapped to ArchiMate 3.0.

Executable binaries identified as Mach-O 64-bit x86_64 executable filetype.

Keras, v. 2.0.4, https://keras.io/, last accessed in November 2017.

Tensorflow v. 1.0.1, https://www.tensorflow.org/.

Scikit-learn, v. 0.19.1, http://scikit-learn.org/stable/modules/tree.html, last accessed in November 2017.

Brückmann, T., Gruhn, V., Pfeiffer, M.: Towards real-time monitoring and controlling of enterprise architectures using business software control centers. In: Crnkovic, I., Gruhn, V., Book, M. (eds.) ECSA 2011. LNCS, vol. 6903, pp. 287–294. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23798-0_31CrossRef

Buschle, M., Ekstedt, M., Grunow, S., Hauder, M., Matthes, F., Roth, S.: Automating enterprise architecture documentation using an enterprise service bus. In: AMCIS 2012 Proceedings. AIS Electronic Library (AISeL) (2012)

Buschle, M., Holm, H., Sommestad, T., Ekstedt, M., Shahzad, K.: A tool for automatic enterprise architecture modeling. In: Nurcan, S. (ed.) CAiSE Forum 2011. LNBIP, vol. 107, pp. 1–15. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29749-6_1CrossRef

Das, S., Dey, A., Pal, A., Roy, N.: Applications of artificial intelligence in machine learning: review and prospect. Int. J. Comput. Appl. 115(9), 31–41 (2015). https://www.ijcaonline.org/archives/volume115/number9/20182-2402

Dijkman, R.M., Pires, L.F., Rinderle-Ma, S. (eds.): 20th IEEE International Enterprise Distributed Object Computing Workshop, EDOC Workshops 2016, Vienna, Austria, 5–9 September 2016. IEEE Computer Society (2016)

Farwick, M., Breu, R., Hauder, M., Roth, S., Matthes, F.: Enterprise architecture documentation: empirical analysis of information sources for automation. In: 2013 46th Hawaii International Conference on System Sciences, pp. 3868–3877 (2013)

Farwick, M., Agreiter, B., Breu, R., Häring, M., Voges, K., Hanschke, I.: Towards living landscape models: automated integration of infrastructure cloud in enterprise architecture management. In: 2010 IEEE 3rd International Conference on Cloud Computing (CLOUD), pp. 35–42. IEEE (2010)

Farwick, M., Schweda, C.M., Breu, R., Hanschke, I.: A situational method for semi-automated enterprise architecture documentation. Softw. Syst. Model. 15(2), 397–426 (2016)CrossRef

Hauder, M., Matthes, F., Roth, S.: Challenges for automated enterprise architecture documentation. In: Aier, S., Ekstedt, M., Matthes, F., Proper, E., Sanz, J.L. (eds.) PRET/TEAR -2012. LNBIP, vol. 131, pp. 21–39. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34163-2_2CrossRef

10.

Holm, H., Buschle, M., Lagerström, R., Ekstedt, M.: Automatic data collection for enterprise architecture models. Softw. Syst. Model. 13(2), 825–841 (2014)CrossRef

11.

Iyer, S., Konstas, I., Cheung, A., Zettlemoyer, L.: Summarizing source code using a neural attention model. In: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, 7–12 August 2016, Berlin, Germany. Long Papers, vol. 1. The Association for Computer Linguistics (2016)

12.

Johnson, P., Ekstedt, M., Lagerström, R.: Automatic probabilistic enterprise IT architecture modeling: a dynamic bayesian networks approach. In: 20th IEEE International Enterprise Distributed Object Computing Workshop, EDOC Workshops 2016, Vienna, Austria, 5–9 September 2016, pp. 1–8 (2016)

13.

Roth, S., Hauder, M., Farwick, M., Breu, R., Matthes, F.: Enterprise architecture documentation: current practices and future directions. In: Wirtschaftsinformatik, p. 58 (2013)

14.

The Open Group: Archimate®3.0.1 specification, an open group standard (2016)

15.

Välja, M., Lagerström, R., Ekstedt, M., Korman, M.: A requirements based approach for automating enterprise it architecture modeling using multiple data sources. In: 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop (EDOCW), pp. 79–87. IEEE (2015)

Titel: A Machine Learning Based Approach to Application Landscape Documentation
verfasst von: Jörg Landthaler
Ömer Uludağ
Gloria Bondel
Ahmed Elnaggar
Saasha Nair
Florian Matthes
Verlag: Springer International Publishing
Buch: The Practice of Enterprise Modeling
Print ISBN: 978-3-030-02301-0

Electronic ISBN: 978-3-030-02302-7

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-030-02302-7_5

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