Results 1 
4 of
4
Causality Closure for a New Class of Curves in RealTime Calculus
"... RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties may then be computed using algebraic techniques in a compositional way. The property of causality on arrival curves essentially characterizes the absence of deadlock in the corresponding generator. A mathematical operation called causality closure transforms arbitrary curves into causal ones. In this paper, we extend the existing theory on causality to the class Upac of infinite curves represented by a finite set of points plus piecewise affine functions, where existing algorithms did not apply. We show how to apply the causality closure on this class of curves, prove that this causal representative is still in the class and give algorithms to compute it. This provides the tightest pair of curves among the curves which accept the same sets of streams.
ac2lus: Bringing SMTsolving and Abstract Interpretation Techniques to RealTime Calculus through the Synchronous Language Lustre
, 2010
"... We present an approach to connect the RealTime Calculus (RTC) method to the synchronous dataflow language Lustre, and its associated toolchain, allowing the use of techniques like SMTsolving and abstract interpretation which were not previously available for use with RTC. The approach is suppo ..."
Abstract
 Add to MetaCart
(Show Context)
We present an approach to connect the RealTime Calculus (RTC) method to the synchronous dataflow language Lustre, and its associated toolchain, allowing the use of techniques like SMTsolving and abstract interpretation which were not previously available for use with RTC. The approach is supported by a tool called ac2lus. It allows to model the system to be analyzed as general Lustre programs with inputs specified by arrival curves; the tool can compute output arrival curves or evaluate upper and lower bounds on any variable of the components, like buffer sizes. Compared to existing approaches to connect RTC to other formalisms, we believe that the use of Lustre, a real programming language, and the synchronous hypothesis make the task easier to write models, and we show that it allows a great flexibility of the tool itself, with many variants to finetune the performances.
(2011)" DOI: 10.1145/2071589.2071590 Causality Closure for a New Class of Curves in RealTime Calculus
, 2011
"... RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties ..."
Abstract
 Add to MetaCart
(Show Context)
RealTime Calculus (RTC) [14] is a framework to analyze heterogeneous realtime systems that process event streams of data. The streams are characterized by arrival curves which express upper and lower bounds on the number of events that may arrive over any specified time interval. System properties may then be computed using algebraic techniques in a compositional way. The property of causality on arrival curves essentially characterizes the absence of deadlock in the corresponding generator. A mathematical operation called causality closure transforms arbitrary curves into causal ones. In this paper, we extend the existing theory on causality to the class Upac of infinite curves represented by a finite set of points plus piecewise affine functions, where existing algorithms did not apply. We show how to apply the causality closure on this class of curves, prove that this causal representative is still in the class and give algorithms to compute it. This provides the tightest pair of curves among the curves which accept the same sets of streams.