TY - CONF AB - Signal regular expressions can specify sequential properties of real-valued signals based on threshold conditions, regular operations, and duration constraints. In this paper we endow them with a quantitative semantics which indicates how robustly a signal matches or does not match a given expression. First, we show that this semantics is a safe approximation of a distance between the signal and the language defined by the expression. Then, we consider the robust matching problem, that is, computing the quantitative semantics of every segment of a given signal relative to an expression. We present an algorithm that solves this problem for piecewise-constant and piecewise-linear signals and show that for such signals the robustness map is a piecewise-linear function. The availability of an indicator describing how robustly a signal segment matches some regular pattern provides a general framework for quantitative monitoring of cyber-physical systems. AU - Bakhirkin, Alexey AU - Ferrere, Thomas AU - Maler, Oded AU - Ulus, Dogan ED - Abate, Alessandro ED - Geeraerts, Gilles ID - 636 SN - 978-331965764-6 TI - On the quantitative semantics of regular expressions over real-valued signals VL - 10419 ER - TY - GEN AB - This book constitutes the refereed proceedings of the 9th InternationalWorkshop on Numerical Software Verification, NSV 2016, held in Toronto, ON, Canada in July 2011 - colocated with CAV 2016, the 28th International Conference on Computer Aided Verification. The NSV workshop is dedicated to the development of logical and mathematical techniques for the reasoning about programmability and reliability. ED - Bogomolov, Sergiy ED - Martel, Matthieu ED - Prabhakar, Pavithra ID - 638 SN - 0302-9743 TI - Numerical Software Verification VL - 10152 ER - TY - CONF AB - Data-independent Memory Hard Functions (iMHFS) are finding a growing number of applications in security; especially in the domain of password hashing. An important property of a concrete iMHF is specified by fixing a directed acyclic graph (DAG) Gn on n nodes. The quality of that iMHF is then captured by the following two pebbling complexities of Gn: – The parallel cumulative pebbling complexity Π∥cc(Gn) must be as high as possible (to ensure that the amortized cost of computing the function on dedicated hardware is dominated by the cost of memory). – The sequential space-time pebbling complexity Πst(Gn) should be as close as possible to Π∥cc(Gn) (to ensure that using many cores in parallel and amortizing over many instances does not give much of an advantage). In this paper we construct a family of DAGs with best possible parameters in an asymptotic sense, i.e., where Π∥cc(Gn) = Ω(n2/ log(n)) (which matches a known upper bound) and Πst(Gn) is within a constant factor of Π∥cc(Gn). Our analysis relies on a new connection between the pebbling complexity of a DAG and its depth-robustness (DR) – a well studied combinatorial property. We show that high DR is sufficient for high Π∥cc. Alwen and Blocki (CRYPTO’16) showed that high DR is necessary and so, together, these results fully characterize DAGs with high Π∥cc in terms of DR. Complementing these results, we provide new upper and lower bounds on the Π∥cc of several important candidate iMHFs from the literature. We give the first lower bounds on the memory hardness of the Catena and Balloon Hashing functions in a parallel model of computation and we give the first lower bounds of any kind for (a version) of Argon2i. Finally we describe a new class of pebbling attacks improving on those of Alwen and Blocki (CRYPTO’16). By instantiating these attacks we upperbound the Π∥cc of the Password Hashing Competition winner Argon2i and one of the Balloon Hashing functions by O (n1.71). We also show an upper bound of O(n1.625) for the Catena functions and the two remaining Balloon Hashing functions. AU - Alwen, Joel F AU - Blocki, Jeremiah AU - Pietrzak, Krzysztof Z ED - Coron, Jean-Sébastien ED - Buus Nielsen, Jesper ID - 640 SN - 978-331956616-0 TI - Depth-robust graphs and their cumulative memory complexity VL - 10212 ER - TY - CONF AB - We introduce two novel methods for learning parameters of graphical models for image labelling. The following two tasks underline both methods: (i) perturb model parameters based on given features and ground truth labelings, so as to exactly reproduce these labelings as optima of the local polytope relaxation of the labelling problem; (ii) train a predictor for the perturbed model parameters so that improved model parameters can be applied to the labelling of novel data. Our first method implements task (i) by inverse linear programming and task (ii) using a regressor e.g. a Gaussian process. Our second approach simultaneously solves tasks (i) and (ii) in a joint manner, while being restricted to linearly parameterised predictors. Experiments demonstrate the merits of both approaches. AU - Trajkovska, Vera AU - Swoboda, Paul AU - Åström, Freddie AU - Petra, Stefanie ED - Lauze, François ED - Dong, Yiqiu ED - Bjorholm Dahl, Anders ID - 641 SN - 978-331958770-7 TI - Graphical model parameter learning by inverse linear programming VL - 10302 ER - TY - GEN AB - Synchronous programs are easy to specify because the side effects of an operation are finished by the time the invocation of the operation returns to the caller. Asynchronous programs, on the other hand, are difficult to specify because there are side effects due to pending computation scheduled as a result of the invocation of an operation. They are also difficult to verify because of the large number of possible interleavings of concurrent asynchronous computation threads. We show that specifications and correctness proofs for asynchronous programs can be structured by introducing the fiction, for proof purposes, that intermediate, non-quiescent states of asynchronous operations can be ignored. Then, the task of specification becomes relatively simple and the task of verification can be naturally decomposed into smaller sub-tasks. The sub-tasks iteratively summarize, guided by the structure of an asynchronous program, the atomic effect of non-atomic operations and the synchronous effect of asynchronous operations. This structuring of specifications and proofs corresponds to the introduction of multiple layers of stepwise refinement for asynchronous programs. We present the first proof rule, called synchronization, to reduce asynchronous invocations on a lower layer to synchronous invocations on a higher layer. We implemented our proof method in CIVL and evaluated it on a collection of benchmark programs. AU - Henzinger, Thomas A AU - Kragl, Bernhard AU - Qadeer, Shaz ID - 6426 SN - 2664-1690 TI - Synchronizing the asynchronous ER -