Formal Verification of Industrial Software and Neural Networks

Software ist ein wichtiger Bestandteil unsere heutige Gesellschaft. Da Software vermehrt in sicherheitskritischen Bereichen angewandt wird, müssen wir uns auf eine korrekte und sichere Ausführung verlassen können. Besonders eingebettete Software, zum Beispiel in medizinischen Geräten, Autos oder Flugzeugen, muss gründlich und formal geprüft werden. Die Software solcher eingebetteten Systeme kann man in zwei Komponenten aufgeteilt. In klassische (deterministische) Steuerungssoftware und maschinelle Lernverfahren zum Beispiel für die Bilderkennung oder Kollisionsvermeidung angewandt werden. Das Ziel dieser Dissertation ist es den Stand der Technik bei der Verifikation von zwei Hauptkomponenten moderner eingebetteter Systeme zu verbessern: in C/C++ geschriebene Software und neuronalen Netze. Für beide Komponenten wird das Verifikationsproblem formal definiert und neue Verifikationsansätze werden vorgestellt

Lange Kohärenzzeit optisch gefangener Ensembles

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Combining Graph-Based and Deduction-Based Information-Flow Analysis

Information flow control (IFC) is a category of techniques for ensuring system security by enforcing information flow properties such as non-interference. Established IFC techniques range from fully automatic approaches with much over-approximation to approaches with high pre- cision but potentially laborious user interaction. A noteworthy approach mitigating the weaknesses of both automatic and interactive IFC tech- niques is the hybrid approach, developed by Küsters et al., which – how- ever – is based on program modifications and still requires a significant amount of user interaction. In this paper, we present a combined approach that works without any program modifications. It minimizes potential user interactions by apply- ing a dependency-graph-based information-flow analysis first. Based on over-approximations, this step potentially generates false positives. Pre- cise non-interference proofs are achieved by applying a deductive theorem prover with a specialized information-flow calculus for checking that no path from a secret input to a public output exists. Both tools are fully integrated into a combined approach, which is evaluated on a case study, demonstrating the feasibility of automatic and precise non-interference proofs for complex programs

Extended coherence time on the clock transition of optically trapped Rubidium

Optically trapped ensembles are of crucial importance for frequency measurements and quantum memories, but generally suffer from strong dephasing due to inhomogeneous density and light shifts. We demonstrate a drastic increase of the coherence time to 21 s on the magnetic field insensitive clock transition of Rb-87 by applying the recently discovered spin self-rephasing. This result confirms the general nature of this new mechanism and thus shows its applicability in atom clocks and quantum memories. A systematic investigation of all relevant frequency shifts and noise contributions yields a stability of 2.4E-11 x tau^(-1/2), where tau is the integration time in seconds. Based on a set of technical improvements, the presented frequency standard is predicted to rival the stability of microwave fountain clocks in a potentially much more compact setup.Comment: 5 pages, 4 figure

Dynamics of Bloch Oscillations in Disordered Lattice Potentials

We present a detailed analysis of the dynamics of Bloch oscillations of Bose-Einstein condensates in disordered lattice potentials. Due to the disorder and the interparticle interactions these oscillations undergo a dephasing, reflected in a damping of the center of mass oscillations, which should be observable under realistic experimental conditions. The interplay between interactions and disorder is far from trivial, ranging from an interaction-enhanced damping due to modulational instability for strong interactions, to an interaction-reduced damping due to a dynamical screening of the disorder potential

Anti-alignments in conformance checking: the dark side of process models

Conformance checking techniques asses the suitability of a process model in representing an underlying process, observed through a collection of real executions. These techniques suffer from the wellknown state space explosion problem, hence handling process models exhibiting large or even infinite state spaces remains a challenge. One important metric in conformance checking is to asses the precision of the model with respect to the observed executions, i.e., characterize the ability of the model to produce behavior unrelated to the one observed. By avoiding the computation of the full state space of a model, current techniques only provide estimations of the precision metric, which in some situations tend to be very optimistic, thus hiding real problems a process model may have. In this paper we present the notion of antialignment as a concept to help unveiling traces in the model that may deviate significantly from the observed behavior. Using anti-alignments, current estimations can be improved, e.g., in precision checking. We show how to express the problem of finding anti-alignments as the satisfiability of a Boolean formula, and provide a tool which can deal with large models efficiently.Peer ReviewedPostprint (author's final draft