Proceedings of the 18th Conference on Computer Science and Intelligence Systems

DOI: http://dx.doi.org/10.15439/2023F4617

Citation: Proceedings of the 18th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 35, pages 141–150 (2023)

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Abstract. Enterprise systems are inherently complex and maintaining their full, up-to-date overview poses a serious challenge to the enterprise architects' teams. This problem encourages the search for automated means of discovering knowledge about such systems. An important aspect of this knowledge is understanding the data that are processed by applications and their relationships. In our previous work, we used application logs of an enterprise system to derive knowledge about the interactions taking place between applications. In this paper, we further explore logs to discover correspondence between data processed by different applications. Our contribution is the following: we propose a method for discovering relationships between data using log analysis, we validate our method against a benchmark system AcmeAir and we validate our method against a real-life system running at Nordea Bank.

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