@inbook{625,
abstract = {In the analysis of reactive systems a quantitative objective assigns a real value to every trace of the system. The value decision problem for a quantitative objective requires a trace whose value is at least a given threshold, and the exact value decision problem requires a trace whose value is exactly the threshold. We compare the computational complexity of the value and exact value decision problems for classical quantitative objectives, such as sum, discounted sum, energy, and mean-payoff for two standard models of reactive systems, namely, graphs and graph games.},
author = {Chatterjee, Krishnendu and Doyen, Laurent and Henzinger, Thomas A},
booktitle = {Models, Algorithms, Logics and Tools},
editor = {Aceto, Luca and Bacci, Giorgio and Ingólfsdóttir, Anna and Legay, Axel and Mardare, Radu},
issn = {03029743},
pages = {367 -- 381},
publisher = {Springer},
title = {{The cost of exactness in quantitative reachability}},
doi = {10.1007/978-3-319-63121-9_18},
volume = {10460},
year = {2017},
}
@inproceedings{631,
abstract = {Template polyhedra generalize intervals and octagons to polyhedra whose facets are orthogonal to a given set of arbitrary directions. They have been employed in the abstract interpretation of programs and, with particular success, in the reachability analysis of hybrid automata. While previously, the choice of directions has been left to the user or a heuristic, we present a method for the automatic discovery of directions that generalize and eliminate spurious counterexamples. We show that for the class of convex hybrid automata, i.e., hybrid automata with (possibly nonlinear) convex constraints on derivatives, such directions always exist and can be found using convex optimization. We embed our method inside a CEGAR loop, thus enabling the time-unbounded reachability analysis of an important and richer class of hybrid automata than was previously possible. We evaluate our method on several benchmarks, demonstrating also its superior efficiency for the special case of linear hybrid automata.},
author = {Bogomolov, Sergiy and Frehse, Goran and Giacobbe, Mirco and Henzinger, Thomas A},
isbn = {978-366254576-8},
location = {Uppsala, Sweden},
pages = {589 -- 606},
publisher = {Springer},
title = {{Counterexample guided refinement of template polyhedra}},
doi = {10.1007/978-3-662-54577-5_34},
volume = {10205},
year = {2017},
}
@inproceedings{633,
abstract = {A Rapidly-exploring Random Tree (RRT) is an algorithm which can search a non-convex region of space by incrementally building a space-filling tree. The tree is constructed from random points drawn from system’s state space and is biased to grow towards large unexplored areas in the system. RRT can provide better coverage of a system’s possible behaviors compared with random simulations, but is more lightweight than full reachability analysis. In this paper, we explore some of the design decisions encountered while implementing a hybrid extension of the RRT algorithm, which have not been elaborated on before. In particular, we focus on handling non-determinism, which arises due to discrete transitions. We introduce the notion of important points to account for this phenomena. We showcase our ideas using heater and navigation benchmarks.},
author = {Bak, Stanley and Bogomolov, Sergiy and Henzinger, Thomas A and Kumar, Aviral},
editor = {Abate, Alessandro and Bodo, Sylvie},
isbn = {978-331963500-2},
location = {Heidelberg, Germany},
pages = {83 -- 89},
publisher = {Springer},
title = {{Challenges and tool implementation of hybrid rapidly exploring random trees}},
doi = {10.1007/978-3-319-63501-9_6},
volume = {10381},
year = {2017},
}
@inproceedings{636,
abstract = {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.},
author = {Bakhirkin, Alexey and Ferrere, Thomas and Maler, Oded and Ulus, Dogan},
editor = {Abate, Alessandro and Geeraerts, Gilles},
isbn = {978-331965764-6},
location = {Berlin, Germany},
pages = {189 -- 206},
publisher = {Springer},
title = {{On the quantitative semantics of regular expressions over real-valued signals}},
doi = {10.1007/978-3-319-65765-3_11},
volume = {10419},
year = {2017},
}
@proceedings{638,
editor = {Bogomolov, Sergiy and Martel, Matthieu and Prabhakar, Pavithra},
publisher = {Springer},
title = {{Numerical Software Verification}},
doi = {10.1007/978-3-319-54292-8},
volume = {10152},
year = {2017},
}