SHARPE at the age of twenty two

Trivedi, K.S.; Sahner, Robin

doi:10.1145/1530873.1530884

Cited by 151 publications

(64 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The same notation is also adopted for IMM and DET transitions, which are associated with Dirac impulse functions f t (y) = δ(y − y) with y = EF T (t) = LF T (t). In particular, we consider the class of piecewise expolynomial PDFs obtained by piecewise composition of products of exponentials and polynomials, on bounded or unbounded supports (also known in the literature as exponomials [14]). …”

Section: Definition 1 An Stpn Is a Tuplementioning

confidence: 99%

“…In this case, due to the memoryless property of the exponential distribution, the underlying stochastic process of the model satisfies the Markov property at each time instant, i.e., the current state provides sufficient information to predict future evolution, regardless of elapsed sojourn times. Efficient algorithms for the analysis of continuous-time Markov chains (CTMCs) can thus be applied to the verification of requirements specified in continuous stochastic logic (CSL), also allowing nesting of temporal operators [11], [12], [13], [9], [14]. Properties specified as deterministic timed automata can also be verified through the analysis of piecewise-deterministic Markov processes resulting from the synchronous composition of the model with the specification automaton [15], [16].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic Model Checking of Regenerative Concurrent Systems

Paolieri

Horváth

Vicario

2016

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

Abstract-We consider the problem of verifying quantitative reachability properties in stochastic models of concurrent activities with generally distributed durations. Models are specified as Stochastic Time Petri Nets (STPNs) and checked against Boolean combinations of interval until operators imposing bounds on the probability that the marking process will satisfy a goal condition at some time in the interval [α, β] after an execution that never violates a safety property. The proposed solution is based on the analysis of regeneration points in the model execution: a regeneration is encountered after a discrete event if the future evolution depends only on the current marking and not on its previous history, thus satisfying the Markov property. We analyze systems in which multiple generally distributed timers can be started or stopped independently, but regeneration points are always encountered with probability 1 after a bounded number of discrete events. Leveraging the properties of regeneration points in probability spaces of execution paths, we show that the problem can be reduced to a set of Volterra integral equations, and we provide algorithms to compute their parameters through the enumeration of finite sequences of stochastic state classes encoding the joint probability density function (PDF) of generally distributed timers after each discrete event. The computation of symbolic PDFs is limited to the first regeneration epoch, and the repetitive structure of the stochastic process is exploited also before the lower bound α, providing crucial benefits for large time bounds. A case study is presented through the probabilistic formulation of Fischer's mutual exclusion protocol, a well-known real-time verification benchmark.

show abstract

Section: Definition 1 An Stpn Is a Tuplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic Model Checking of Regenerative Concurrent Systems

Paolieri

Horváth

Vicario

2016

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

show abstract

“…However, more complex reliability models are still compatible with our approach because the model complexity does not impact on the context modeling, whereas it obviously affects: the number of UML annotations, the complexity of the reliability model extraction from the UML model, and the reliability model solution. In such cases, more complex tools, such as SHARPE [47], can be adopted for reliability analysis.…”

Section: Context-aware Transient-state Reliability Analysismentioning

confidence: 99%

Multidimensional context modeling applied to non-functional analysis of software

et al. 2017

View full text Add to dashboard Cite

Context awareness is a first-class attribute of today software systems. Indeed, many applications need to be aware of their context in order to adapt their structure and behavior for offering the best quality of service even in case the software and hardware resources are limited. Modeling the context, its evolution, and its influence on the services provided by (possibly resource constrained) applications are becoming primary activities throughout the whole software life cycle, although it is still difficult to capture the multidimensional nature of context. We propose a framework for modeling and reasoning on the context and its evolution along multiple dimensions. Our approach enables (1) the representation of dependencies among heterogeneous context attributes through a formally defined semantics for attribute composition and (2) the stochastic analysis of context evolution. As a result, context can be part of a model-based software development process, and multidimensional context analysis can be used for different purposes, such as non-functional analysis. We demonstrate how certain types of analysis, not feasible with context-agnostic approaches, are enabled in our framework by explicitly representing the interplay between context evolution and non-functional attributes. Such analyses allow the identification of critical aspects or design errors that may not emerge without jointly taking into account multiple context attributes. The framework is shown at work on a case study in the eHealth domain.

show abstract

“…There are numerous software packages available to evaluate SRN models. The authors have used SHARPE [9] and SPNP [10] to evaluate the SRN in this paper. These packages use the given model to generate a reachability graph of the system, based on the transitions, places, arcs and defined reward functions.…”

Section: System Availability Modelmentioning

confidence: 99%

Availability and resiliency analysis of modern distribution grids using stochastic reward nets

Morris

Kim

Wood

et al. 2017

2017 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia)

View full text Add to dashboard Cite

Abstract-This paper presents a method to evaluate the availability and resiliency of a modern distribution grid using Stochastic Reward Nets (SRNs). SRNs are a modelling formalism used to evaluate the complex dependencies of components during fault recovery. The method is verified using the RBTS Bus 2 Test system and then applied to an enhanced version of the distribution grid which employs remote communications and distribution automation to hasten the recovery process. Sensitivity analysis is applied to the enhanced version of the test system to demonstrate improvements in recovery time and reduction in downtime with respect to to component failure. Finally, resiliency analysis is performed to the enhanced system to evaluate the systems ability to recover from abnormal and severe events and demonstrate the improvements that this technology provides.

show abstract

SHARPE at the age of twenty two

Cited by 151 publications

References 31 publications

Probabilistic Model Checking of Regenerative Concurrent Systems

Probabilistic Model Checking of Regenerative Concurrent Systems

Multidimensional context modeling applied to non-functional analysis of software

Availability and resiliency analysis of modern distribution grids using stochastic reward nets

Contact Info

Product

Resources

About