586 research outputs found
Testing real-time systems using TINA
The paper presents a technique for model-based black-box conformance testing of real-time systems using the Time Petri Net Analyzer TINA. Such test suites are derived from a prioritized time Petri net composed of two concurrent sub-nets specifying respectively the expected behaviour of the system under test and its environment.We describe how the toolbox TINA has been extended to support automatic generation of time-optimal test suites. The result is optimal in the sense that the set of test cases in the test suite have the shortest possible accumulated time to be executed. Input/output conformance serves as the notion of implementation correctness, essentially timed trace inclusion taking environment assumptions into account. Test cases selection is based either on using manually formulated test purposes or automatically from various coverage criteria specifying structural criteria of the model to be fulfilled by the test suite. We discuss how test purposes and coverage criterion are specified in the linear temporal logic SE-LTL, derive test sequences, and assign verdicts
Schedulability analysis of timed CSP models using the PAT model checker
Timed CSP can be used to model and analyse real-time and concurrent behaviour of embedded control systems. Practical CSP implementations combine the CSP model of a real-time control system with prioritized scheduling to achieve efficient and orderly use of limited resources. Schedulability analysis of a timed CSP model of a system with respect to a scheduling scheme and a particular execution platform is important to ensure that the system design satisfies its timing requirements. In this paper, we propose a framework to analyse schedulability of CSP-based designs for non-preemptive fixed-priority multiprocessor scheduling. The framework is based on the PAT model checker and the analysis is done with dense-time model checking on timed CSP models. We also provide a schedulability analysis workflow to construct and analyse, using the proposed framework, a timed CSP model with scheduling from an initial untimed CSP model without scheduling. We demonstrate our schedulability analysis workflow on a case study of control software design for a mobile robot. The proposed approach provides non-pessimistic schedulability results
Incremental Sampling-based Algorithm for Minimum-violation Motion Planning
This paper studies the problem of control strategy synthesis for dynamical
systems with differential constraints to fulfill a given reachability goal
while satisfying a set of safety rules. Particular attention is devoted to
goals that become feasible only if a subset of the safety rules are violated.
The proposed algorithm computes a control law, that minimizes the level of
unsafety while the desired goal is guaranteed to be reached. This problem is
motivated by an autonomous car navigating an urban environment while following
rules of the road such as "always travel in right lane'' and "do not change
lanes frequently''. Ideas behind sampling based motion-planning algorithms,
such as Probabilistic Road Maps (PRMs) and Rapidly-exploring Random Trees
(RRTs), are employed to incrementally construct a finite concretization of the
dynamics as a durational Kripke structure. In conjunction with this, a weighted
finite automaton that captures the safety rules is used in order to find an
optimal trajectory that minimizes the violation of safety rules. We prove that
the proposed algorithm guarantees asymptotic optimality, i.e., almost-sure
convergence to optimal solutions. We present results of simulation experiments
and an implementation on an autonomous urban mobility-on-demand system.Comment: 8 pages, final version submitted to CDC '1
Fair Simulation for Nondeterministic and Probabilistic Buechi Automata: a Coalgebraic Perspective
Notions of simulation, among other uses, provide a computationally tractable
and sound (but not necessarily complete) proof method for language inclusion.
They have been comprehensively studied by Lynch and Vaandrager for
nondeterministic and timed systems; for B\"{u}chi automata the notion of fair
simulation has been introduced by Henzinger, Kupferman and Rajamani. We
contribute to a generalization of fair simulation in two different directions:
one for nondeterministic tree automata previously studied by Bomhard; and the
other for probabilistic word automata with finite state spaces, both under the
B\"{u}chi acceptance condition. The former nondeterministic definition is
formulated in terms of systems of fixed-point equations, hence is readily
translated to parity games and is then amenable to Jurdzi\'{n}ski's algorithm;
the latter probabilistic definition bears a strong ranking-function flavor.
These two different-looking definitions are derived from one source, namely our
coalgebraic modeling of B\"{u}chi automata. Based on these coalgebraic
observations, we also prove their soundness: a simulation indeed witnesses
language inclusion
Survey on Directed Model Checking
International audienceThis article surveys and gives historical accounts to the algorithmic essentials of directed model checking, a promising bug-hunting technique to mitigate the state explosion problem. In the enumeration process, successor selection is prioritized. We discuss existing guidance and methods to automatically generate them by exploiting system abstractions. We extend the algorithms to feature partial-order reduction and show how liveness problems can be adapted by lifting the search Space. For deterministic, finite domains we instantiate the algorithms to directed symbolic, external and distributed search. For real-time domains we discuss the adaption of the algorithms to timed automata and for probabilistic domains we show the application to counterexample generation. Last but not least, we explain how directed model checking helps to accelerate finding solutions to scheduling problems
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