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Preoteasa V.,Aalto University | Dragomir I.,Verimag | Tripakis S.,Aalto University | Tripakis S.,University of California at Berkeley
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2017

Simulink is a de-facto industrial standard for embedded system design. In previous work, we developed a compositional analysis framework for Simulink, the Refinement Calculus of Reactive Systems (RCRS), which allows checking compatibility and substitutability of components. However, standard type checking was not considered in that work. In this paper we present a method for the type inference of Simulink models using the Isabelle theorem prover. A Simulink diagram is translated into an (RCRS) Isabelle theory. Then Isabelle’s powerful type inference mechanism is used to infer the types of the diagram based on the types of the basic blocks. One of the aims is to handle formally as many diagrams as possible. In particular, we want to be able to handle even those diagrams that may have typing ambiguities, provided that they are accepted by Simulink. This method is implemented in our toolset that translates Simulink diagrams into Isabelle theories and simplifies them. We evaluate our technique on several case studies, most notably, an automotive fuel control system benchmark provided by Toyota. © IFIP International Federation for Information Processing 2017.


Dang T.,French National Center for Scientific Research | Maler O.,French National Center for Scientific Research | Testylier R.,VERIMAG
HSCC'10 - Proceedings of the 13th ACM International Conference on Hybrid Systems: Computation and Control | Year: 2010

This paper is concerned with reachable set computation for non-linear systems using hybridization. The essence of hybridization is to approximate a non-linear vector field by a simpler (such as affine) vector field. This is done by partitioning the state space into small regions within each of which a simpler vector field is defined. This approach relies on the availability of methods for function approximation and for handling the resulting dynamical systems. Concerning function approximation using interpolation, the accuracy depends on the shapes and sizes of the regions which can compromise as well the speed of reachability computation since it may generate spurious classes of trajectories. In this paper we study the relationship between the region geometry and reachable set accuracy and propose a method for constructing hybridization regions using tighter interpolation error bounds. In addition, our construction exploits the dynamics of the system to adapt the orientation of the regions, in order to achieve better time-efficiency. We also present some experimental results on a high-dimensional biological system, to demonstrate the performance improvement. © 2010 ACM.


von Essen C.,Verimag | Giannakopoulou D.,NASA
International Journal on Software Tools for Technology Transfer | Year: 2015

The next generation airborne collision avoidance system, ACAS X, departs from the traditional deterministic model on which the current system, TCAS, is based. To increase robustness, ACAS X relies on probabilistic models to represent the various sources of uncertainty. The work reported in this paper identifies verification challenges for ACAS X, and studies the applicability of probabilistic verification and synthesis techniques in addressing these challenges. Due to shortcomings of off-the-shelf probabilistic analysis tools, we developed a new framework, named VeriCA (Verification for Collision Avoidance). VeriCA is a combined probabilistic synthesis and verification framework that is custom designed for ACAS X and systems with similar characteristics. VeriCA supports Java as a modeling language, is memory efficient, employs parallelization, and provides an interactive simulator that displays aircraft encounters and the corresponding ACAS X behavior. We describe the application of our framework to ACAS X, together with the results and recommendations that our analysis produced. © 2015 Springer-Verlag Berlin Heidelberg (outside the USA)


Dang T.,VERIMAG | Gawlitza T.M.,VERIMAG
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Over-approximating the set of all reachable states of a given system is an important task for the verification of safety properties. Such an unbounded time verification is in particular challenging for hybrid systems. We recently developed an algorithm that over-approximates the set of all reachable states of a given affine hybrid automata by performing linear template-based abstract interpretation [4]. In this article we extend the previous results by adding uncertainty to the model of affine hybrid automata. Uncertainty can be used for abstracting the behavior of non-linear hybrid systems. We adapt our techniques to this model and show that, w.r.t. given linear templates, the abstract reachability problem is still in coNP by reducing abstract reachability for affine hybrid automata with uncertainty to abstract reachability for affine programs (affine hybrid automata where only discrete transitions are allowed). We thus provide a new connection between a continuous time model and a purely discrete model. © 2011 Springer-Verlag.


Von Essen C.,Verimag | Giannakopoulou D.,NASA
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014

The next generation airborne collision avoidance system, ACAS X, departs from the traditional deterministic model on which the current system, TCAS, is based. To increase robustness, ACAS X relies on probabilistic models to represent the various sources of uncertainty. The work reported in this paper identifies verification challenges for ACAS X, and studies the applicability of probabilistic verification and synthesis techniques in addressing these challenges. Due to shortcomings of off-the-shelf probabilistic analysis tools, we developed a framework that is designed to handle systems with similar characteristics as ACAS X. We describe the application of our framework to AC © 2014 Springer-Verlag.


Donze A.,Verimag | Clermont G.,University of Pittsburgh | Langmead C.J.,Carnegie Mellon University
Journal of Computational Biology | Year: 2010

The dynamics of biological processes are often modeled as systems of nonlinear ordinary differential equations (ODE). An important feature of nonlinear ODEs is that seemingly minor changes in initial conditions or parameters can lead to radically different behaviors. This is problematic because in general it is never possible to know/measure the precise state of any biological system due to measurement errors. The parameter synthesis problem is to identify sets of parameters (including initial conditions) for which a given system of nonlinear ODEs does not reach a given set of undesirable states. We present an efficient algorithm for solving this problem that combines sensitivity analysis with an efficient search over initial conditions. It scales to high-dimensional models and is exact if the given model is affine. We demonstrate our method on different models of the acute inflammatory response to bacterial infection, and identify initial conditions consistent with three biologically relevant outcomes. © Copyright 2010, Mary Ann Liebert, Inc.


Sifakis J.,Verimag
Proceedings -Design, Automation and Test in Europe, DATE | Year: 2011

Traditional engineering disciplines such as civil or mechanical engineering are based on solid theory for building artefacts with predictable behavior over their lifetime. In contrast, we lack similar constructivity results for computing systems engineering: computer science provides only partial answers to particular system design problems. With few exceptions, predictability is impossible to guarantee at design time and therefore, a posteriori verification remains the only means for ensuring their correct operation. © 2011 EDAA.


Gawlitza T.M.,VERIMAG | Seidl H.,TU Munich
ACM Transactions on Programming Languages and Systems | Year: 2011

We present practical algorithms for computing exact least solutions of equation systems over the reals with addition, multiplication by positive constants, minimum and maximum. The algorithms are based on strategy iteration. Our algorithms can, for instance, be used for the analysis of recursive stochastic games. In the present article we apply our techniques for computing abstract least fixpoint semantics of affine programs over the relational template polyhedra domain. In particular, we thus obtain practical algorithms for computing abstract least fixpoint semantics over the abstract domains of intervals, zones, and octagons. © 2011 ACM.


Pavlinovic Z.,New York University | King T.,Verimag | Wies T.,New York University
Proceedings of the ACM SIGPLAN International Conference on Functional Programming, ICFP | Year: 2015

Compilers for statically typed functional programming languages are notorious for generating confusing type error messages. When the compiler detects a type error, it typically reports the program location where the type checking failed as the source of the error. Since other error sources are not even considered, the actual root cause is often missed. A more adequate approach is to consider all possible error sources and report the most useful one subject to some usefulness criterion. In our previous work, we showed that this approach can be formulated as an optimization problem related to satisfiability modulo theories (SMT). This formulation cleanly separates the heuristic nature of usefulness criteria from the underlying search problem. Unfortunately, algorithms that search for an optimal error source cannot directly use principal types which are crucial for dealing with the exponential-time complexity of the decision problem of polymorphic type checking. In this paper, we present a new algorithm that efficiently finds an optimal error source in a given ill-typed program. Our algorithm uses an improved SMT encoding to cope with the high complexity of polymorphic typing by iteratively expanding the typing constraints from which principal types are derived. The algorithm preserves the clean separation between the heuristics and the actual search. We have implemented our algorithm for OCaml. In our experimental evaluation, we found that the algorithm reduces the running times for optimal type error localization from minutes to seconds and scales better than previous localization algorithms. © 2015 ACM.


Dang T.,Verimag | Gawlitza T.M.,Verimag | Gawlitza T.M.,University of Sydney
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

Computing over-approximations of all possible time trajectories is an important task in the analysis of hybrid systems. Sankaranarayanan et al. [20] suggested to approximate the set of reachable states using template polyhedra. In the present paper, we use a max-strategy improvement algorithm for computing an abstract semantics for affine hybrid automata that is based on template polyhedra and safely over-approximates the concrete semantics. Based on our formulation, we show that the corresponding abstract reachability problem is in co-NP. Moreover, we obtain a polynomial-time algorithm for the time elapse operation over template polyhedra. © 2011 Springer-Verlag.

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