11,791 research outputs found
Mightyl: A compositional translation from mitl to timed automata
Metric Interval Temporal Logic (MITL) was first proposed in the early 1990s as a specification formalism for real-time systems. Apart from its appealing intuitive syntax, there are also theoretical evidences that make MITL a prime real-time counterpart of Linear Temporal Logic (LTL). Unfortunately, the tool support for MITL verification is still lacking to this day. In this paper, we propose a new construction from MITL to timed automata via very-weak one-clock alternating timed automata. Our construction subsumes the well-known construction from LTL to BĂĽchi automata by Gastin and Oddoux and yet has the additional benefits of being compositional and integrating easily with existing tools. We implement the construction in our new tool MightyL and report on experiments using Uppaal and LTSmin as back-ends
Compositional Verification for Timed Systems Based on Automatic Invariant Generation
We propose a method for compositional verification to address the state space
explosion problem inherent to model-checking timed systems with a large number
of components. The main challenge is to obtain pertinent global timing
constraints from the timings in the components alone. To this end, we make use
of auxiliary clocks to automatically generate new invariants which capture the
constraints induced by the synchronisations between components. The method has
been implemented in the RTD-Finder tool and successfully experimented on
several benchmarks
Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking
This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications
A Forward Reachability Algorithm for Bounded Timed-Arc Petri Nets
Timed-arc Petri nets (TAPN) are a well-known time extension of the Petri net
model and several translations to networks of timed automata have been proposed
for this model. We present a direct, DBM-based algorithm for forward
reachability analysis of bounded TAPNs extended with transport arcs, inhibitor
arcs and age invariants. We also give a complete proof of its correctness,
including reduction techniques based on symmetries and extrapolation. Finally,
we augment the algorithm with a novel state-space reduction technique
introducing a monotonic ordering on markings and prove its soundness even in
the presence of monotonicity-breaking features like age invariants and
inhibitor arcs. We implement the algorithm within the model-checker TAPAAL and
the experimental results document an encouraging performance compared to
verification approaches that translate TAPN models to UPPAAL timed automata.Comment: In Proceedings SSV 2012, arXiv:1211.587
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