Mixing logics and rewards for the component-oriented specification of performance measures

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Title: Mixing logics and rewards for the component-oriented specification of performance measures
Authors: Aldini, Alessandro aldini@sti.uniurb.it, Bernardo, Marco1
Source: Theoretical Computer Science. Aug2007, Vol. 382 Issue 1, p3-23. 21p.
Subjects: Stochastic processes, Algebra, Markov processes, Computer science research, Mathematical analysis
Abstract: Formal notations for system performance modeling need to be equipped with suitable notations for specifying performance measures. These companion notations have been traditionally based on reward structures and, more recently, on temporal logics. In this paper we propose an approach that combines logics and rewards, together with a definition mechanism that allows performance measures to be specified in a component-oriented way, thus facilitating the task for non-experts. The resulting Measure Specification Language (MSL) is interpreted both on action-labeled continuous-time Markov chains and on stochastic process algebras. The latter interpretation provides a compositional framework for performance-sensitive model manipulations and emphasizes the increased expressiveness with respect to traditional reward structures for implicit-state modeling notations. [Copyright &y& Elsevier]
Copyright of Theoretical Computer Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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An: 26038635
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  Data: Formal notations for system performance modeling need to be equipped with suitable notations for specifying performance measures. These companion notations have been traditionally based on reward structures and, more recently, on temporal logics. In this paper we propose an approach that combines logics and rewards, together with a definition mechanism that allows performance measures to be specified in a component-oriented way, thus facilitating the task for non-experts. The resulting Measure Specification Language (MSL) is interpreted both on action-labeled continuous-time Markov chains and on stochastic process algebras. The latter interpretation provides a compositional framework for performance-sensitive model manipulations and emphasizes the increased expressiveness with respect to traditional reward structures for implicit-state modeling notations. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Theoretical Computer Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.tcs.2007.05.006
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      – SubjectFull: Markov processes
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              Text: Aug2007
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