SPADES - a process algebra for discrete event simulation

Harrison, Peter G.

doi:10.1093/logcom/10.1.3

Cited by 80 publications

(36 citation statements)

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“…The subject of formalizing DES has been studied extensively (Smith 2003). From early formal models based on FSA (Ramadge and Wonham 1989) and stochastic process (Glynn 1989), to DEVS (Zeigler et al 2000), to Petri Net based (Zhou and Venkatesh 1999), and to recent process algebra based formalisms (D'Argenio et al 1998;Harrison and Strulo 2000). The focus of modeling simulation systems has been gradually shifting from quantitative analysis to behavioral analysis due to the fast increasing of system complexity and requirement of adaptive structures.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, it only has a non-deterministic construct (choice) without probability. Recently, several stochastic extensions have been proposed to handle probability and time duration (D'Argenio et al 1998;Harrison and Strulo 2000;Priami 1995) by introducing new probability and timed constructs. In next section, a general theory of modeling systems using Pi-calculus and a formal definition of PiDES are proposed.…”

Section: X(y)mentioning

confidence: 99%

“…Therefore, it is often more important to study how the components of the systems interact with each other. As a result, logical models, with minimum or no quantitative properties, such as Finite State Automata (FSA) (Ramadge and Wonham 1989), Discrete Event System Specification (DEVS) (Zeigler et al 2000), Petri Nets (Zhou and Venkatesh 1999), and process algebra (D'Argenio et al 1998;Harrison and Strulo 2000), have become quite popular for these types of models. These formalisms provide rigorous semantics and powerful mathematical tools for building and analyzing simulation models.…”

Section: Introductionmentioning

confidence: 99%

“…SPADE (Harrison and Strulo 2000) and ♠ (D' Argenio et al 1998) may be improved to support many of the above features, but they are relatively new and need further study.…”

Section: Introductionmentioning

confidence: 99%

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A Pi-calculus formalism for discrete event simulation

Wang¹,

Wysk²

2008

2008 Winter Simulation Conference

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This paper presents PiDES, a formalism for discrete event simulation based on Pi-calculus. PiDES provides a rigorous semantics of behavior modeling and coordination for simulation federates. The capability of PiDES is demonstrated by translating a generalized semi-Markov process formalism into PiDES specification. The usage of PiDES is illustrated through a case study of a flexible manufacturing system consisting of two machines, two parts, and a robot. The major advantages of PiDES are discussed, which include: a) a complete set of semantics for both modeling and execution; b) supporting parallel and distributed simulation; c) adaptive modeling; d) rich coordination semantics for developing large simulation systems; and finally e) a formalism that can be used for agent-based simulation. An implementation of PiDES using Java programming language is also provided.

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Section: Discussionmentioning

confidence: 99%

Section: X(y)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…SPADE (Harrison and Strulo 2000) and ♠ (D' Argenio et al 1998) may be improved to support many of the above features, but they are relatively new and need further study.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Pi-calculus formalism for discrete event simulation

Wang¹,

Wysk²

2008

2008 Winter Simulation Conference

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“…Thus, stochastic extensions of classical formal models, as process algebras and Petri Nets, have appeared in the literature (see e.g. [1,2,5,7,11,12,14,16,20]). As we have shown in the previous example, the main idea underlying stochastic models is that time information is incremented with some kind of probabilistic information.…”

Section: Introductionmentioning

confidence: 99%

Towards Testing Stochastic Timed Systems

Núñez

Rodrı́guez

2003

Formal Techniques for Networked and Distributed Systems - FORTE 2003

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Abstract. In this paper we present a first approach to the definition of conformance testing relations for systems presenting stochastic timed behavior. By stochastic time we mean that the probability of performing an event may vary according to the elapsed time. In particular, we will consider delays specified by means of random variables. In order to define our formal model, we will provide a stochastic extension of the notion of finite state machine. We will give a first implementation relation and we will discuss its practical drawbacks. That is, we will show that this relation cannot be appropriately checked under a black/grey-box testing methodology. We will also present other alternative implementation relations that can be checked up to a certain degree of confidence. We will define test cases and how they are applied to implementations. Finally, we will give a test generation algorithm providing complete, up to a degree of confidence, test suites.

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A formal framework to test soft and hard deadlines in timed systems

Merayo

Núñez

Rodrı́guez

2011

Software Testing Verif & Rel

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This paper introduces a formal framework to specify and test systems presenting both soft and hard deadlines. While hard deadlines must always be met on time, soft deadlines can be sometimes met in a different time, usually greater, from the specified one. It is this characteristic (to formally define sometimes) that produces several reasonable alternatives to define appropriate implementation relations, that is, relations to decide whether an implementation is correct with respect to a specification. In addition to introducing these relations, the paper also presents a formal testing framework to test implementations and provides an algorithm to derive sound and complete test suites with respect to the implementation relations previously defined. That is, an implementation conforms to a specification if and only if the implementation successfully passes all the tests belonging to the suite derived from the specification. Definition 4Let M = (S, I, O, T r, s in ) be an IFSM. A timed trace, or simply trace, of M is a tuple (s, s , (i 1 /o 1 , . . .,i r /o r ), d) if there exist transitions (s 1 , s 2 , i 1 , o 1 , d 1 ), . . ., (s r , s r+1 , i r , o r , d r ) ∈ Tr, such that s = s 1 , s = s r+1 , and d = d i . The sequence (i 1 /o 1 , . . .,i r /o r ) is a non-timed evolution, or simply evolution, of M if (s in , s , (i 1 /o 1 , . . .,i r /o r ), d) is a trace of M for some d ∈ I R + and s ∈ S. NTEvol(M) denotes the set of non-timed evolutions of M.588 M. G. MERAYO, M. NÚÑEZ AND I. RODRÍGUEZ dist(C, d) = r∈C dist(r, d) 2 592 A FORMAL FRAMEWORK TO TEST SOFT AND HARD DEADLINES from up(r, d) = 0ifr ≤ a 2

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SPADES - a process algebra for discrete event simulation

Cited by 80 publications

References 0 publications

A Pi-calculus formalism for discrete event simulation

A Pi-calculus formalism for discrete event simulation

Towards Testing Stochastic Timed Systems

A formal framework to test soft and hard deadlines in timed systems

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