Specifying properties can be challenging work. In this paper, we propose an automated approach to exemplify properties given in the form of automata extended with timing constraints and timing parameters, and that can also encode... more
Specifying properties can be challenging work. In this paper, we propose an automated approach to exemplify properties given in the form of automata extended with timing constraints and timing parameters, and that can also encode constraints over real-valued signals. That is, given such a specification and given an admissible automaton for each signal, we output concrete runs exemplifying real (or impossible) runs for this specification. Specifically, our method takes as input a specification, and a set of admissible behaviors, all given as a subclass of rectangular hybrid automata, namely timed automata extended with arbitrary clock rates, signal constraints, and timing parameters. Our method then generates concrete runs exemplifying the specification.
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Given a log and a specification, timed pattern matching aims at exhibiting for which start and end dates a specification holds on that log. For example, “a given action is always followed by another action before a given deadline”. This... more
Given a log and a specification, timed pattern matching aims at exhibiting for which start and end dates a specification holds on that log. For example, “a given action is always followed by another action before a given deadline”. This problem has strong connections with monitoring real-time systems. We address here timed pattern matching in the presence of an uncertain specification, i. e., that may contain timing parameters (e. g., the deadline can be uncertain or unknown). We want to know for which start and end dates, and for what values of the timing parameters, a property holds. For instance, we look for the minimum or maximum deadline (together with the corresponding start and end dates) for which the property holds. We propose two frameworks for parametric timed pattern matching. The first one is based on parametric timed model checking. In contrast to most parametric timed problems, the solution is effectively computable. The second one is a dedicated method; not only we l...
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Data for "Exemplifying parametric timed specifications over signals with bounded behavior" See README.md in the zipped file for explanations and instructions for reproductibility.
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This is the source code for the experiments in our paper "Model-Bounded Monitoring of Hybrid Systems" published at ICCPS 2021.
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The synthesis problem of a cyber-physical system (CPS) is to find an input signal under which the system's behavior satisfies a given specification. Our setting is that the specification is a formula of signal temporal logic, and... more
The synthesis problem of a cyber-physical system (CPS) is to find an input signal under which the system's behavior satisfies a given specification. Our setting is that the specification is a formula of signal temporal logic, and furthermore, that the specification is a conjunction of different and often conflicting requirements. Conjunctive specifications are often challenging for optimization-based falsification -- an established method for CPS analysis that can also be used for synthesis -- since the usual framework (especially how its robust semantics handles Boolean connectives) is not suited for finding delicate trade-offs between different requirements. Our proposed method consists of the combination of optimization-based falsification and constrained optimization. Specifically, we show that the state-of-the-art multiple constraint ranking method can be combined with falsification powered by CMA-ES optimization; its performance advantage is demonstrated in experiments.
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The synthesis problem of a cyber-physical system (CPS) is to find an input signal under which the system's behavior satisfies a given specification. Our setting is that the specification is a formula of signal temporal logic, and... more
The synthesis problem of a cyber-physical system (CPS) is to find an input signal under which the system's behavior satisfies a given specification. Our setting is that the specification is a formula of signal temporal logic, and furthermore, that the specification is a conjunction of different and often conflicting requirements. Conjunctive specifications are often challenging for optimization-based falsification -- an established method for CPS analysis that can also be used for synthesis -- since the usual framework (especially how its robust semantics handles Boolean connectives) is not suited for finding delicate trade-offs between different requirements. Our proposed method consists of the combination of optimization-based falsification and constrained optimization. Specifically, we show that the state-of-the-art multiple constraint ranking method can be combined with falsification powered by CMA-ES optimization; its performance advantage is demonstrated in experiments.
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We present a method to extract a weighted finite automaton (WFA) from a recurrent neural network (RNN). Our method is based on the WFA learning algorithm by Balle and Mohri, which is in turn an extension of Angluin's classic L*... more
We present a method to extract a weighted finite automaton (WFA) from a recurrent neural network (RNN). Our method is based on the WFA learning algorithm by Balle and Mohri, which is in turn an extension of Angluin's classic L* algorithm. Our technical novelty is in the use of regression methods for the so-called equivalence queries, thus exploiting the internal state space of an RNN to prioritize counterexample candidates. This way we achieve a quantitative/weighted extension of the recent work by Weiss, Goldberg and Yahav that extracts DFAs. We experimentally evaluate the accuracy, expressivity and efficiency of the extracted WFAs.
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This report presents the results from the 2021 friendly competition in the ARCH work- shop for the falsification of temporal logic specifications over Cyber-Physical Systems. We briefly describe the competition settings, which have been... more
This report presents the results from the 2021 friendly competition in the ARCH work- shop for the falsification of temporal logic specifications over Cyber-Physical Systems. We briefly describe the competition settings, which have been inherited from the previ- ous years, give background on the participating teams and tools and discuss the selected benchmarks. Apart from new requirements and participants, the major novelty in this instalment is that falsifying inputs have been validated independently. During this pro- cess, we uncovered several issues like configuration errors and computational discrepancies, stressing the importance of this kind of validation.