@inproceedings{6035,
abstract = {We present JuliaReach, a toolbox for set-based reachability analysis of dynamical systems. JuliaReach consists of two main packages: Reachability, containing implementations of reachability algorithms for continuous and hybrid systems, and LazySets, a standalone library that implements state-of-the-art algorithms for calculus with convex sets. The library offers both concrete and lazy set representations, where the latter stands for the ability to delay set computations until they are needed. The choice of the programming language Julia and the accompanying documentation of our toolbox allow researchers to easily translate set-based algorithms from mathematics to software in a platform-independent way, while achieving runtime performance that is comparable to statically compiled languages. Combining lazy operations in high dimensions and explicit computations in low dimensions, JuliaReach can be applied to solve complex, large-scale problems.},
author = {Bogomolov, Sergiy and Forets, Marcelo and Frehse, Goran and Potomkin, Kostiantyn and Schilling, Christian},
booktitle = {Proceedings of the 22nd International Conference on Hybrid Systems: Computation and Control},
isbn = {9781450362825},
keyword = {reachability analysis, hybrid systems, lazy computation},
location = {Montreal, QC, Canada},
pages = {39--44},
publisher = {ACM},
title = {{JuliaReach: A toolbox for set-based reachability}},
doi = {10.1145/3302504.3311804},
volume = {22},
year = {2019},
}
@inproceedings{6042,
abstract = {Static program analyzers are increasingly effective in checking correctness properties of programs and reporting any errors found, often in the form of error traces. However, developers still spend a significant amount of time on debugging. This involves processing long error traces in an effort to localize a bug to a relatively small part of the program and to identify its cause. In this paper, we present a technique for automated fault localization that, given a program and an error trace, efficiently narrows down the cause of the error to a few statements. These statements are then ranked in terms of their suspiciousness. Our technique relies only on the semantics of the given program and does not require any test cases or user guidance. In experiments on a set of C benchmarks, we show that our technique is effective in quickly isolating the cause of error while out-performing other state-of-the-art fault-localization techniques.},
author = {Christakis, Maria and Heizmann, Matthias and Mansur, Muhammad Numair and Schilling, Christian and Wüstholz, Valentin},
booktitle = {25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems },
location = {Prague, Czech Republic},
pages = {226--243},
publisher = {Springer Nature},
title = {{Semantic fault localization and suspiciousness ranking}},
doi = {10.1007/978-3-030-17462-0_13},
volume = {11427},
year = {2019},
}
@inproceedings{6493,
abstract = {We present two algorithmic approaches for synthesizing linear hybrid automata from experimental data. Unlike previous approaches, our algorithms work without a template and generate an automaton with nondeterministic guards and invariants, and with an arbitrary number and topology of modes. They thus construct a succinct model from the data and provide formal guarantees. In particular, (1) the generated automaton can reproduce the data up to a specified tolerance and (2) the automaton is tight, given the first guarantee. Our first approach encodes the synthesis problem as a logical formula in the theory of linear arithmetic, which can then be solved by an SMT solver. This approach minimizes the number of modes in the resulting model but is only feasible for limited data sets. To address scalability, we propose a second approach that does not enforce to find a minimal model. The algorithm constructs an initial automaton and then iteratively extends the automaton based on processing new data. Therefore the algorithm is well-suited for online and synthesis-in-the-loop applications. The core of the algorithm is a membership query that checks whether, within the specified tolerance, a given data set can result from the execution of a given automaton. We solve this membership problem for linear hybrid automata by repeated reachability computations. We demonstrate the effectiveness of the algorithm on synthetic data sets and on cardiac-cell measurements.},
author = {Garcia Soto, Miriam and Henzinger, Thomas A and Schilling, Christian and Zeleznik, Luka},
booktitle = {31st International Conference on Computer-Aided Verification},
isbn = {9783030255398},
issn = {0302-9743},
keyword = {Synthesis, Linear hybrid automaton, Membership},
location = {New York City, NY, USA},
pages = {297--314},
publisher = {Springer},
title = {{Membership-based synthesis of linear hybrid automata}},
doi = {10.1007/978-3-030-25540-4_16},
volume = {11561},
year = {2019},
}
@inproceedings{1227,
abstract = {Many biological systems can be modeled as multiaffine hybrid systems. Due to the nonlinearity of multiaffine systems, it is difficult to verify their properties of interest directly. A common strategy to tackle this problem is to construct and analyze a discrete overapproximation of the original system. However, the conservativeness of a discrete abstraction significantly determines the level of confidence we can have in the properties of the original system. In this paper, in order to reduce the conservativeness of a discrete abstraction, we propose a new method based on a sufficient and necessary decision condition for computing discrete transitions between states in the abstract system. We assume the state space partition of a multiaffine system to be based on a set of multivariate polynomials. Hence, a rectangular partition defined in terms of polynomials of the form (xi − c) is just a simple case of multivariate polynomial partition, and the new decision condition applies naturally. We analyze and demonstrate the improvement of our method over the existing methods using some examples.},
author = {Kong, Hui and Bartocci, Ezio and Bogomolov, Sergiy and Grosu, Radu and Henzinger, Thomas A and Jiang, Yu and Schilling, Christian},
location = {Grenoble, France},
pages = {128 -- 144},
publisher = {Springer},
title = {{Discrete abstraction of multiaffine systems}},
doi = {10.1007/978-3-319-47151-8_9},
volume = {9957},
year = {2016},
}
@inproceedings{1134,
abstract = {Hybrid systems have both continuous and discrete dynamics and are useful for modeling a variety of control systems, from air traffic control protocols to robotic maneuvers and beyond. Recently, numerous powerful and scalable tools for analyzing hybrid systems have emerged. Several of these tools implement automated formal methods for mathematically proving a system meets a specification. This tutorial session will present three recent hybrid systems tools: C2E2, HyST, and TuLiP. C2E2 is a simulated-based verification tool for hybrid systems, and uses validated numerical solvers and bloating of simulation traces to verify systems meet specifications. HyST is a hybrid systems model transformation and translation tool, and uses a canonical intermediate representation to support most of the recent verification tools, as well as automated sound abstractions that simplify verification of a given hybrid system. TuLiP is a controller synthesis tool for hybrid systems, where given a temporal logic specification to be satisfied for a system (plant) model, TuLiP will find a controller that meets a given specification. © 2016 IEEE.},
author = {Duggirala, Parasara and Fan, Chuchu and Potok, Matthew and Qi, Bolun and Mitra, Sayan and Viswanathan, Mahesh and Bak, Stanley and Bogomolov, Sergiy and Johnson, Taylor and Nguyen, Luan and Schilling, Christian and Sogokon, Andrew and Tran, Hoang and Xiang, Weiming},
booktitle = {2016 IEEE Conference on Control Applications},
location = {Buenos Aires, Argentina },
publisher = {IEEE},
title = {{Tutorial: Software tools for hybrid systems verification transformation and synthesis C2E2 HyST and TuLiP}},
doi = {10.1109/CCA.2016.7587948},
year = {2016},
}
@inproceedings{1605,
abstract = {Multiaffine hybrid automata (MHA) represent a powerful formalism to model complex dynamical systems. This formalism is particularly suited for the representation of biological systems which often exhibit highly non-linear behavior. In this paper, we consider the problem of parameter identification for MHA. We present an abstraction of MHA based on linear hybrid automata, which can be analyzed by the SpaceEx model checker. This abstraction enables a precise handling of time-dependent properties. We demonstrate the potential of our approach on a model of a genetic regulatory network and a myocyte model.},
author = {Bogomolov, Sergiy and Schilling, Christian and Bartocci, Ezio and Batt, Grégory and Kong, Hui and Grosu, Radu},
location = {Haifa, Israel},
pages = {19 -- 35},
publisher = {Springer},
title = {{Abstraction-based parameter synthesis for multiaffine systems}},
doi = {10.1007/978-3-319-26287-1_2},
volume = {9434},
year = {2015},
}
@misc{1500,
abstract = {In this poster, we present methods for randomly generating hybrid automata with affine differential equations, invariants, guards, and assignments. Selecting an arbitrary affine function from the set of all affine functions results in a low likelihood of generating hybrid automata with diverse and interesting behaviors, as there are an uncountable number of elements in the set of all affine functions. Instead, we partition the set of all affine functions into potentially interesting classes and randomly select elements from these classes. For example, we partition the set of all affine differential equations by using restrictions on eigenvalues such as those that yield stable, unstable, etc. equilibrium points. We partition the components describing discrete behavior (guards, assignments, and invariants) to allow either time-dependent or state-dependent switching, and in particular provide the ability to generate subclasses of piecewise-affine hybrid automata. Our preliminary experimental results with a prototype tool called HyRG (Hybrid Random Generator) illustrate the feasibility of this generation method to automatically create standard hybrid automaton examples like the bouncing ball and thermostat.},
author = {Nguyen, Luan V and Christian Schilling and Sergiy Bogomolov and Johnson, Taylor T},
booktitle = {HSCC: Hybrid Systems - Computation and Control},
pages = {289 -- 290},
publisher = {Springer},
title = {{Poster: HyRG: A random generation tool for affine hybrid automata}},
doi = {10.1145/2728606.2728650},
year = {2015},
}