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.

Abstract4Application logs record the behavior of a system during its runtime and their analysis can provide useful information.In this article, we propose a method of automated log analysis to discover interactions taking place between applications in an enterprise.We believe that such an automated approach can greatly support enterprise architects in building an up-to-date view of a governed system in a modern, fast-paced development environment.Our contribution is the following: we propose a new method for log template generation called SLT (Simple Log Template), we propose a method of extracting knowledge about application interactions from logs, and we validate the proposed methods on a real system running at Nordea Bank.Additionally, we collect statistical information about application logs from the real-life system, based on which we formulate some observations that support our method. Discovering interactions between applications with log analysis