Thomas Schmitz

Thomas Schmitz, Jean-Jacques Embrechts

Numerous audio systems for musicians are expensive and bulky. Therefore, it could be advantageous to model them and to replace them by computer emulation. In guitar players' world, audio systems could have a desirable nonlinear behavior (distortion effects). It is thus difficult to find a simple model to emulate them in real time. Volterra series model and its subclass are usual ways to model nonlinear systems. Unfortunately, these systems are difficult to identify in an analytic way. In this paper we propose to take advantage of the new progress made in neural networks to emulate them in real time. We show that an accurate emulation can be reached with less than 1% of root mean square error between the signal coming from a tube amplifier and the output of the neural network. Moreover, the research has been extended to model the Gain parameter of the amplifier.

Kalev Alpernas, Cormac Flanagan, Sadjad Fouladi et al.

The rise of serverless computing provides an opportunity to rethink cloud security. We present an approach for securing serverless systems using a novel form of dynamic information flow control (IFC). We show that in serverless applications, the termination channel found in most existing IFC systems can be arbitrarily amplified via multiple concurrent requests, necessitating a stronger termination-sensitive non-interference guarantee, which we achieve using a combination of static labeling of serverless processes and dynamic faceted labeling of persistent data. We describe our implementation of this approach on top of JavaScript for AWS Lambda and OpenWhisk serverless platforms, and present three realistic case studies showing that it can enforce important IFC security properties with low overhead.

Dietmar Jannach, Thomas Schmitz

A number of automated techniques and tools were proposed in the research literature over the years which aim to support the spreadsheet developer in the process of testing and debugging a faulty spreadsheet. One underlying assumption of many of these approaches is that the spreadsheet developer is capable of providing test cases or is at least reliably able to determine whether a calculated value in a certain cell is correct given the current set of inputs. Since real-world spreadsheets can be complex, we argue that these assumptions might be too strong in some situations. We therefore propose to support the user during testing and debugging by automatically computing spreadsheet fragments of manageable size. The spreadsheet developer can then verify the correctness of a smaller set of formulas for which the calculated output can be more easily validated.