Challenges for modeling and simulation methods in systems biology
Proceedings of the 38th conference on Winter simulation
Better Quality in Synthesis through Quantitative Objectives
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Probabilistic Weighted Automata
CONCUR 2009 Proceedings of the 20th International Conference on Concurrency Theory
Quantitative generalizations of languages
DLT'07 Proceedings of the 11th international conference on Developments in language theory
Energy and mean-payoff games with imperfect information
CSL'10/EACSL'10 Proceedings of the 24th international conference/19th annual conference on Computer science logic
Quantitative multi-objective verification for probabilistic systems
TACAS'11/ETAPS'11 Proceedings of the 17th international conference on Tools and algorithms for the construction and analysis of systems: part of the joint European conferences on theory and practice of software
Measuring and synthesizing systems in probabilistic environments
CAV'10 Proceedings of the 22nd international conference on Computer Aided Verification
Assume-Guarantee verification for probabilistic systems
TACAS'10 Proceedings of the 16th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Ariadne: dominance checking of nonlinear hybrid automata using reachability analysis
RP'12 Proceedings of the 6th international conference on Reachability Problems
Quantitative reactive modeling and verification
Computer Science - Research and Development
Compositional probabilistic verification through multi-objective model checking
Information and Computation
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We present a compositional theory of system verification, where specifications assign real-numbered costs to systems. These costs can express a wide variety of quantitative system properties, such as resource consumption, price, or a measure of how well a system satisfies its specification. The theory supports the composition of systems and specifications, and the hiding of variables. Boolean refinement relations are replaced by real-numbered distances between descriptions of a system at different levels of detail. We show that the classical boolean rules for compositional reasoning have quantitative counterparts in our setting. While our general theory allows costs to be specified by arbitrary cost functions, we also consider a class of linear cost functions, which give rise to an instance of our framework where all operations are computable in polynomial time.