Graph mining algorithms are able to discover frequent subgraphs within a database of graphs. Such algorithms facilitate a number of novel possibilities of data analysis in domains where data is usually not numerical or text-based but is available in a structured form. A typical domain of application is the analysis of chemical molecules, which can be represented as well as transportation networks or workflows as graphs. At the IPD, an approach was developed recently as an application in software engineering which is able to localise certain software bugs based on the analysis of dynamic call graphs. In this approach, it is in particular challenging to integrate structural graph-based information with numerical data and to scale for large graphs. In the current research, we work on enhancements of our approach as well on its generalisation for further domains of application. In a cooperation with the chair for computer architecture, we apply graph mining in a completely new domain, the analysis of static control flow graphs for supporting the decision which computer architecture to use.