Because Android apps are written in Java and executed on a virtual machine (VM), there is an opportunity to employ Java Pathfinder (JPF) for their verification. There already exist two JPF extensions, jpf-android and jpf-pathdroid. The former executes Java bytecode on the Java VM, while the latter executes Android applications in their original format. Both do not support native methods, and thus depend on a model of the Android environment. This paper introduces an alternative approach: we run JPF as an Android application that executes Java bytecode, which gives us direct access to the Android environment. This approach allows us to verify rich Android apps that rely on native calls

Many text mining tools cannot be applied directly to documents available on web pages. There are tools for fetching and preprocessing of textual data, but combining them with the data processing tool into one working tool chain can be time consuming. The preprocessing task is even more labor-intensive if documents are located on multiple remote sources with different storage formats.In this paper, we propose the simplification of data preparation process for cases when data come from wide range of web resources. We developed an open-source tool, called Kayur, that greatly minimizes time and effort required for routine data preprocessing steps, allowing to quickly proceed to the main task of data analysis. The datasets generated by the tool are ready to be loaded into a data mining workbench, such as WEKA or Carrot2, to perform classification, feature prediction, and other data mining tasks.

Many text mining tools cannot be applied directly to documents available on web pages. There are tools for fetching and preprocessing of textual data, but combining them with the data processing tool into one working tool chain can be time consuming. The preprocessing task is even more labor-intensive if documents are located on multiple remote sources with different storage formats. In this paper, we propose the simplification of data preparation process for cases when data come from wide range of web resources. We developed an open-source tool, called Kayur, that greatly minimizes time and effort required for routine data preprocessing steps, allowing to quickly proceed to the main task of data analysis. The datasets generated by the tool are ready to be loaded into a data mining workbench, such as WEKA or Carrot2, to perform classification, feature prediction, and other data mining tasks.