On the solution of GSPN reward models
Performance Evaluation
A compositional approach to performance modelling
A compositional approach to performance modelling
Performance measure sensitive congruences for Markovian process algebras
Theoretical Computer Science
Stochastic Process Algebra: From an Algebraic Formalism to an Architectural Description Language
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
PRISM: Probabilistic Symbolic Model Checker
TOOLS '02 Proceedings of the 12th International Conference on Computer Performance Evaluation, Modelling Techniques and Tools
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
The Möbius Modeling Environment: Recent Developments
QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
On the usability of process algebra: an architectural view
Theoretical Computer Science - Process algebra
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Model checking expected time and expected reward formulae with random time bounds
Computers & Mathematics with Applications
A methodology based on formal methods for predicting the impact of dynamic power management
SFM-Moby'05 Proceedings of the 5th international conference on Formal Methods for the Design of Computer, Communication, and Software Systems: mobile computing
Performability measure specification: combining CSRL and MSL
FMICS'11 Proceedings of the 16th international conference on Formal methods for industrial critical systems
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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.