J. A. López

Jorge López, Maxime Labonne, Claude Poletti

In order to properly train a machine learning model, data must be properly collected. To guarantee a proper data collection, verifying that the collected data set holds certain properties is a possible solution. For example, guaranteeing that the data set contains samples across the whole input space, or that the data set is balanced w.r.t. different classes. We present a formal approach for verifying a set of arbitrarily stated properties over a data set. The proposed approach relies on the transformation of the data set into a first order logic formula, which can be later verified w.r.t. the different properties also stated in the same logic. A prototype tool, which uses the z3 solver, has been developed; the prototype can take as an input a set of properties stated in a formal language and formally verify a given data set w.r.t. to the given set of properties. Preliminary experimental results show the feasibility and performance of the proposed approach, and furthermore the flexibility for expressing properties of interest.

Erick Petersen, Jorge López, Natalia Kushik et al.

This paper presents the design and architecture of a network emulator whose links' parameters (such as delay and bandwidth) vary at different time instances. The emulator can thus be used in order to test and evaluate novel solutions for such networks, before their final deployment. To achieve this goal, different existing technologies are carefully combined to emulate link dynamicity, automatic traffic generation, and overall network device emulation. The emulator takes as an input a formal model of the network to emulate and configures all required software to execute live software instances of the desired network components, in the requested topology. We devote our study to the so-called dynamic link networks, with potentially asymmetric links. Since emulating asymmetric dynamic links is far from trivial (even with the existing state-of-the-art tools), we provide a detailed design architecture that allows this. As a case study, a satellite network emulation is presented. Experimental results show the precision of our dynamic assignments and the overall flexibility of the proposed solution.