Optimized Temporal Monitors for SystemC

Tabakov, Deian; Vardi, Moshe Y.

doi:10.1007/978-3-642-16612-9_33

Cited by 24 publications

(27 citation statements)

References 29 publications

(36 reference statements)

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“…First, there is related work on BBC itself: [27,30,34]. Second, we mention monitoring [41], adaptive learning [13,17] and learning ωregular languages [2,26] as related research directions with a different focus. Third, other than the LearnLib there is another active learning framework called libalf [6].…”

Section: Related Workmentioning

confidence: 99%

Sound black-box checking in the LearnLib

Meijer

Pol

2019

Innovations Syst Softw Eng

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In black-box checking (BBC) incremental hypotheses on the behavior of a system are learned in the form of finite automata, using information from a given set of requirements, specified in Linear-time Temporal Logic (LTL). The LTL formulae are checked on intermediate automata and potential counterexamples are validated on the actual system. Spurious counterexamples are used by the learner to refine these automata. We improve BBC in two directions. First, we improve checking lasso-like counterexamples by assuming a check for state equivalence. This provides a sound method without knowing an upper-bound on the number of states in the system. Second, we propose to check the safety portion of an LTL property first, by deriving simple counterexamples using monitors. We extended LearnLib's system under learning API to make our methods accessible, using LTSmin as model checker under the hood. We illustrate how LearnLib's most recent active learning algorithms can be used for BBC in practice. Using the RERS 2017 challenge, we provide experimental results on the performance of all LearnLib's active learning algorithms when applied in a BBC setting. We will show that the novel incremental algorithms TTT and ADT perform the best. We also provide experiments on the efficiency of various BBC strategies.

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Section: Related Workmentioning

confidence: 99%

Sound black-box checking in the LearnLib

Meijer

Pol

2019

Innovations Syst Softw Eng

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“…Though specifications including past time operators may be natural for some other domains [19], flight rules require future-time reasoning. To enable more intuitive specifications, others have studied monitoring of future-time claims; see [22] for a survey and [5,11,14,21,27,28] for algorithms and frameworks. Most of these observer algorithms, however, were designed with a software implementation in mind and require a powerful computer.…”

Section: Related Workmentioning

confidence: 99%

Temporal-Logic Based Runtime Observer Pairs for System Health Management of Real-Time Systems

Reinbacher

Rozier

Schumann

2014

Lecture Notes in Computer Science

107

116

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We propose a real-time, Realizable, Responsive, Unobtrusive Unit (rt-R2U2) to meet the emerging needs for System Health Management (SHM) of new safety-critical embedded systems like automated vehicles, Unmanned Aerial Systems (UAS), or small satellites. SHM for these systems must be able to handle unexpected situations and adapt specifications quickly during flight testing between closely-timed consecutive missions, not mid-mission, necessitating fast reconfiguration. They must enable more advanced probabilistic reasoning for diagnostics and prognostics while running aboard limited hardware without affecting the certified on-board software. We define and prove correct translations of two real-time projections of Linear Temporal Logic to two types of efficient observer algorithms to continuously assess the status of the system. A synchronous observer yields an instant abstraction of the satisfaction check, whereas an asynchronous observer concretizes this abstraction at a later, a priori known, time. By feeding the system's real-time status into a statistical reasoning unit, e.g., based on Bayesian networks, we enable advanced health estimation and diagnosis. We experimentally demonstrate our novel framework on real flight data from NASA's Swift UAS. By on-boarding rt-R2U2 aboard an existing FPGA already built into the standard UAS design and seamlessly intercepting sensor values through readonly observations of the system bus, we avoid system integration problems of software instrumentation or added hardware. The flexibility of our approach with regard to changes in the monitored specification is not due to the reconfigurability offered by FPGAs; it is a benefit of the modularity of our observers and would also be available on non-reconfigurable hardware platforms such as ASICs.

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“…Combination of symbolic techniques in automata-theoretic setting and compiler optimization techniques have also been explored to optimize runtime overheads of temporal monitors. Along this line, [133] proposed an approach for reducing overheads of runtime monitors for SystemC program. Here, overhead optimization is achieved by means of symbolic representations of both state and alphabet of the monitor, Satisfiability-Modulo-Theory solver, and state-folding technique.…”

Section: Overhead Reductionmentioning

confidence: 99%

A Study on Run Time Assurance for Complex Cyber Physical Systems

Koutsoukos¹,

Porter²,

Kumar³

et al. 2013

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Optimized Temporal Monitors for SystemC

Cited by 24 publications

References 29 publications

Sound black-box checking in the LearnLib

Sound black-box checking in the LearnLib

Temporal-Logic Based Runtime Observer Pairs for System Health Management of Real-Time Systems

A Study on Run Time Assurance for Complex Cyber Physical Systems

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