Diagnosis with Petri Net Unfoldings

Haar, Stefan; Fabre, Éric

doi:10.1007/978-1-4471-4276-8_15

“…With respect to the techniques we use, our work is clearly related to works on diagnosis in discrete event systems [5,21] and specifically diagnosis via unfolding [9]. The diagnosis questions in these works are actually very different from ours.…”

Section: Related Workmentioning

confidence: 99%

Fault Ascription in Concurrent Systems

Gößler

¹

,

Stefani

²

2016

Trustworthy Global Computing

View full text Add to dashboard Cite

Fault diagnosis is becoming increasingly important and difficult with the growing pervasiveness and complexity of computer systems. We propose in this paper a general semantic framework for fault ascription, a precise form of fault diagnosis that relies on counterfactual analysis for identifying necessary and sufficient causes of faults in component-based systems. Our framework relies on configuration structures to handle concurrent systems, partial and distributed observations in a uniform way. It defines basic conditions for a counterfactual analysis of necessary and sufficient causes, and it presents a refined analysis that conforms to our basic conditions while avoiding various infelicities.

show abstract

“…With respect to the techniques we use, our work is clearly related to works on diagnosis in discrete event systems [5,21] and specifically diagnosis via unfolding [9]. The diagnosis questions in these works are actually very different from ours.…”

Section: Examplesmentioning

confidence: 99%

“…Several approaches to fault diagnosis have been put forward in the literature, e.g. using techniques from artificial intelligence [17,16], from automatic control [12], or from concurrency theory [3,9].…”

Section: Introductionmentioning

confidence: 99%

Trustworthy Global Computing

Ganty¹,

Loreti²

2016

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Fault diagnosis is becoming increasingly important and difficult with the growing pervasiveness and complexity of computer systems. We propose in this paper a general semantic framework for fault ascription, a precise form of fault diagnosis that relies on counterfactual analysis for identifying necessary and sufficient causes of faults in component-based systems. Our framework relies on configuration structures to handle concurrent systems, partial and distributed observations in a uniform way. It defines basic conditions for a counterfactual analysis of necessary and sufficient causes, and it presents a refined analysis that conforms to our basic conditions while avoiding various infelicities.

show abstract

“…Rather than diagnosis itself, numerous contributions have considered the diagnosability property, which means that the presence of a fault can be detected in bounded time after its occurrence. Diagnosability has been studied for numerous models (automata [1], [3], Petri nets [5], concurrent systems [6], [7], visibly push-down automata [8]...). It has been extended to stochastic systems [9]- [15], and to distributed or decentralized settings.…”

Section: Introductionmentioning

confidence: 99%

Diagnosability degree of stochastic discrete event systems

Bazille

¹

,

Fabre

²

,

Genest

³

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

Abstract-Diagnosability is the ability to detect a fault from partial observations collected on a system. It has been studied for numerous models of discrete event systems, but essentially from a logical perspective. This paper explores quantitative versions of the problem, to evaluate "how much" a system is (non-)diagnosable. For the diagnosable part of a system, that we characterize, we then examine the probability distribution of the detection delay. We show that the mean and the standard deviation of the detection delay can be easily evaluated.

show abstract

Diagnosis with Petri Net Unfoldings

Cited by 6 publications

References 34 publications

Fault Ascription in Concurrent Systems

Fault Ascription in Concurrent Systems

Trustworthy Global Computing

Diagnosability degree of stochastic discrete event systems

Contact Info

Product

Resources

About