From LTL to rLTL monitoring: improved monitorability through robust semantics

Mascle, Corto; Neider, Daniel; Schwenger, Maximilian; Tabuada, Paulo; Weinert, Alexander; Zimmermann, Martín

doi:10.1007/s10703-022-00398-4

Cited by 4 publications

(2 citation statements)

References 58 publications

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“…Temporal logics are widely used in many domains as they allow the formalisation of time dependent properties. For example in philosophy temporal logics can be used to reason about issues involving the temporal domain [28], in computer science and specifically, in monitoring, temporal logics are used to specify and monitor specific properties of a system [21,6], in complex event processing or recognition [12,3,7]-which is the focus of this work-temporal logics are used for specifying temporal phenomena and detecting them in streams of information. Naturally, each temporal logic comes with its own focus and limitations.…”

Section: Introductionmentioning

confidence: 99%

Handling of Past and Future with Phenesthe+

Pitsikalis,

Lisitsa,

Totzke

2023

Electron. Proc. Theor. Comput. Sci.

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Writing temporal logic formulae for properties that combine instantaneous events with overlapping temporal phenomena of some duration is difficult in classical temporal logics. To address this issue, in previous work we introduced a new temporal logic with intuitive temporal modalities specifically tailored for the representation of both instantaneous and durative phenomena. We also provided an implementation of a complex event processing system, Phenesthe, based on this logic, that has been applied and tested on a real maritime surveillance scenario.In this work, we extend our temporal logic with two extra modalities to increase its expressive power for handling future formulae. We compare the expressive power of different fragments of our logic with Linear Temporal Logic and dyadic first-order logic. Furthermore, we define correctness criteria for stream processors that use our language. Last but not least, we evaluate empirically the performance of Phenesthe+, our extended implementation, and show that the increased expressive power does not affect efficiency significantly.

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Section: Introductionmentioning

confidence: 99%

Handling of Past and Future with Phenesthe+

Pitsikalis,

Lisitsa,

Totzke

2023

Electron. Proc. Theor. Comput. Sci.

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“…One of rLTL's key features is its syntactic similarity to LTL, which allows for a seamless and transparent transition from specifications expressed in LTL to specifications expressed in rLTL. Moreover, it is worth mentioning that rLTL has spawned numerous follow-up works, including rLTL model checking [2,3,4], rLTL runtime monitoring [20], and robust extensions of prompt LTL and Linear Dynamic Logic [24,25].…”

Section: Introductionmentioning

confidence: 99%

Robustness-by-Construction Synthesis: Adapting to the Environment at Runtime

Nayak

Neider

Zimmermann

2022

Lecture Notes in Computer Science

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While most of the current synthesis algorithms only focus on correctness-by-construction, ensuring robustness has remained a challenge.Hence, in this paper, we address the robust-by-construction synthesis problem by considering the specifications to be expressed by a robust version of Linear Temporal Logic (LTL), called robust LTL (rLTL). rLTL has a many-valued semantics to capture different degrees of satisfaction of a specification, i.e., satisfaction is a quantitative notion.We argue that the current algorithms for rLTL synthesis do not compute optimal strategies in a non-antagonistic setting. So, a natural question is whether there is a way of satisfying the specification "better" if the environment is indeed not antagonistic. We address this question by developing two new notions of strategies. The first notion is that of adaptive strategies, which, in response to the opponent's non-antagonistic moves, maximize the degree of satisfaction. The idea is to monitor non-optimal moves of the opponent at runtime using multiple parity automata and adaptively change the system strategy to ensure optimality. The second notion is that of strongly adaptive strategies, which is a further refinement of the first notion. These strategies also maximize the opportunities for the opponent to make non-optimal moves. We show that computing such strategies for rLTL specifications is not harder than the standard synthesis problem, e.g., computing strategies with LTL specifications, and takes doubly-exponential time.

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Robust computation tree logic

Nayak,

Neider,

Roy

et al. 2024

Innovations Syst Softw Eng

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It is widely accepted that every system should be robust in that “small” violations of environment assumptions should lead to “small” violations of system guarantees, but it is less clear how to make this intuition mathematically precise. While significant efforts have been devoted to providing notions of robustness for linear temporal logic, branching-time logics, such as computation tree logic (CTL) and CTL*, have received less attention in this regard. To address this shortcoming, we develop “robust” extensions of CTL and CTL*, which we name robust CTL (rCTL) and robust CTL* (rCTL*). Both extensions are syntactically similar to their parent logics but employ multi-valued semantics to distinguish between “large” and “small” violations of the specification. We show that the multi-valued semantics of rCTL make it more expressive than CTL, while rCTL* is as expressive as CTL*. Moreover, we show that the model checking problem, the satisfiability problem, and the synthesis problem for rCTL and rCTL* have the same asymptotic complexity as their non-robust counterparts, implying that robustness can be added to branching-time logics for free.

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From LTL to rLTL monitoring: improved monitorability through robust semantics

Cited by 4 publications

References 58 publications

Handling of Past and Future with Phenesthe+

Handling of Past and Future with Phenesthe+

Robustness-by-Construction Synthesis: Adapting to the Environment at Runtime

Robust computation tree logic

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