The Temporal Mobile Stochastic Logic (MoSL) has been introduced in previous works by the authors for formulating properties of systems specified in StoKlaim, a Markovian extension of Klaim. The main purpose of MoSL is addressing key functional aspects of network aware programming such as distribution awareness, mobility and security and to guarantee their integration with performance and dependability guarantees. In this paper we present SoSL, a variant of MoSL, designed for dealing with specific features of Service-Oriented Computing (SOC). We also show how SoSL formulae can be model-checked against systems descriptions expressed with MarCaSPiS, a process calculus designed for addressing quantitative aspects of SOC. In order to perform actual model checking, we rely on a dedicated front-end that uses existing state-based stochastic model-checkers, like e.g. the Markov Reward Model Checker (MRMC).

SoSL: A Service-Oriented Stochastic LogicRigorous Software Engineering for Service-Oriented Systems / Rocco Nicola;Diego Latella;Michele Loreti;Mieke Massink. - STAMPA. - (2011), pp. 447-466. [10.1007/978-3-642-20401-2_21]

SoSL: A Service-Oriented Stochastic LogicRigorous Software Engineering for Service-Oriented Systems

LORETI, MICHELE;
2011

Abstract

The Temporal Mobile Stochastic Logic (MoSL) has been introduced in previous works by the authors for formulating properties of systems specified in StoKlaim, a Markovian extension of Klaim. The main purpose of MoSL is addressing key functional aspects of network aware programming such as distribution awareness, mobility and security and to guarantee their integration with performance and dependability guarantees. In this paper we present SoSL, a variant of MoSL, designed for dealing with specific features of Service-Oriented Computing (SOC). We also show how SoSL formulae can be model-checked against systems descriptions expressed with MarCaSPiS, a process calculus designed for addressing quantitative aspects of SOC. In order to perform actual model checking, we rely on a dedicated front-end that uses existing state-based stochastic model-checkers, like e.g. the Markov Reward Model Checker (MRMC).
2011
9783642204005
9783642204012
Lecture Notes in Computer Science, Rigorous Software Engineering for Service-Oriented Systems
447
466
Rocco Nicola;Diego Latella;Michele Loreti;Mieke Massink
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/602017
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