A Formally Verified Monitor for Metric First-Order Temporal Logic

Schneider, Joshua; Basin, David; Krstić, Srđan; Traytel, Dmitriy

doi:10.1007/978-3-030-32079-9_18

Cited by 23 publications

(23 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar work on verifying dynamic programming monitors for LTL that uses the Isabelle/HOL proof assistant [33] is also limited to finite traces. Isabelle/HOL is used in [35] to extract certifiably-correct monitoring code from specifications expressed in Metric First-Order Temporal Logic (MFOTL). Although MFOTL uses quantifications over event data (similar to ours), the analysis in [35] is limited to formulas that are satisfied by finitely-many valuations; our techniques do not have this restriction.…”

Section: Resultsmentioning

confidence: 99%

“…Isabelle/HOL is used in [35] to extract certifiably-correct monitoring code from specifications expressed in Metric First-Order Temporal Logic (MFOTL). Although MFOTL uses quantifications over event data (similar to ours), the analysis in [35] is limited to formulas that are satisfied by finitely-many valuations; our techniques do not have this restriction. Further afield, the work in [31] uses symbolic analysis and SMT solvers to reason about the runtime monitoring of contracts.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

On Implementing Symbolic Controllability

Francalanza¹,

Xuereb²

2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Runtime Monitors observe the execution of a system with the aim of reaching a verdict about it. One property that is expected of monitors is consistent verdict detections; this property was characterised in prior work via a symbolic analysis called symbolic controllability. This paper explores whether the proposed symbolic analysis lends itself well to the construction of a tool that checks monitors for this deterministic behaviour. We implement a prototype that automates this symbolic analysis, and establish complexity upper bounds for the algorithm used. We also consider a number of optimisations for the implemented prototype, and assess the potential gains against benchmark monitors.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

On Implementing Symbolic Controllability

Francalanza¹,

Xuereb²

2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…The R2U2 [27,35] tool in particular implements mtl monitors on fpga while allowing for future-time specifications. Further, there are approaches for generating verified monitors for logics [2,34].…”

Section: Bibliographic Remarksmentioning

confidence: 99%

Monitoring Cyber-Physical Systems: From Design to Integration

Schwenger

2020

Runtime Verification

View full text Add to dashboard Cite

Cyber-physical systems are inherently safety-critical. The deployment of a runtime monitor significantly increases confidence in their safety. The effectiveness of the monitor can be maximized by considering it an integral component during its development. Thus, in this paper, I given an overview over recent work regarding a development process for runtime monitors alongside a cyber-physical system. This process includes the transformation of desirable safety properties into the formal specification language RTLola. A compiler then generates an executable artifact for monitoring the specification. This artifact can then be integrated into the system.

show abstract

“…The safety assumption requires that any negated subformula is guarded by a non-negated subformula, such that ϕ can be monitored using finite relations [14,54]. (Safe formulas are called monitorable in these references.)…”

Section: Lemmamentioning

confidence: 99%

“…Both our implementation [53] and formalization [55] are publicly available. The formal verification of an MFOTL monitor modeled after MonPoly has been addressed in a separate line of work [11,54].…”

Section: Introductionmentioning

confidence: 99%

Scalable Online First-Order Monitoring

Schneider

Basin

Brix

et al. 2018

Runtime Verification

Self Cite

View full text Add to dashboard Cite

Online monitoring is the task of identifying complex temporal patterns while incrementally processing streams of data-carrying events. Existing state-of-the-art monitors for first-order patterns, which may refer to and quantify over data values, can process streams of modest velocity in real-time. We show how to scale up first-order monitoring to substantially higher velocities by slicing the stream, based on the events' data values, into substreams that can be monitored independently. Because monitoring is not embarrassingly parallel in general, slicing can lead to data duplication. To reduce this overhead, we adapt hash-based partitioning techniques from databases to the monitoring setting. We implement these techniques in an automatic data slicer based on Apache Flink and empirically evaluate its performance using two tools-MonPoly and DejaVu-to monitor the substreams. Our evaluation attests to substantial scalability improvements for both tools.

show abstract

A Formally Verified Monitor for Metric First-Order Temporal Logic

Cited by 23 publications

References 24 publications

On Implementing Symbolic Controllability

On Implementing Symbolic Controllability

Monitoring Cyber-Physical Systems: From Design to Integration

Scalable Online First-Order Monitoring

Contact Info

Product

Resources

About