ASE

Machine Learning (ML) can be used to analyze and classify large collections of graph-based information, e.g. images, location information, the structure of molecules and proteins, ... Graph kernels is one of the ML techniques typically used for such ...

Cooperating cyber-physical systems-of-systems (CO-CPS) such as vehicle platoons, robot teams or drone swarms usually have strict safety requirements on both spatial and temporal behavior. Learning-based testing is a combination of machine learning and ...

Testing is the most widely employed method to find vulnerabilities in real-world software programs. Compositional analysis, based on symbolic execution, is an automated testing method to find vulnerabilities in medium- to large-scale programs consisting ...

In this work we tackle the problem of binary code similarity by using deep learning applied to binary code visualization techniques. Our idea is to represent binaries as images and then to investigate whether it is possible to recognize similar binaries ...

Code search and comprehension have become more difficult in recent years due to the rapid expansion of available source code. Current tools lack a way to label arbitrary code at scale while maintaining up-to-date representations of new programming ...

In this paper, we present an approach for the fast deployment and efficient scoring of Support Vector Machine (SVM) models. We developed a compiler for transforming a formal specification of a SVM and generating source code in different versions of the ...