Probabilistic non-determinism
Model-checking continuous-time Markov chains
ACM Transactions on Computational Logic (TOCL)
Reduction and Refinement Strategies for Probabilistic Analysis
PAPM-PROBMIV '02 Proceedings of the Second Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Reachability Analysis of Probabilistic Systems by Successive Refinements
PAPM-PROBMIV '01 Proceedings of the Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Reduction and Refinement Strategies for Probabilistic Analysis
PAPM-PROBMIV '02 Proceedings of the Second Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Probabilistic Verification of Discrete Event Systems Using Acceptance Sampling
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Abstraction, Refinement And Proof For Probabilistic Systems (Monographs in Computer Science)
Abstraction, Refinement And Proof For Probabilistic Systems (Monographs in Computer Science)
Abstract interpretation of programs as Markov decision processes
Science of Computer Programming - Special issue: Static analysis symposium (SAS 2003)
On finite-state approximants for probabilistic computation tree logic
Theoretical Computer Science - Quantitative aspects of programming languages (QAPL 2004)
Game-based Abstraction for Markov Decision Processes
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
Probabilistic Model Checking Modulo Theories
QEST '07 Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems
Comparative branching-time semantics for Markov chains
Information and Computation
Three-valued abstraction for continuous-time Markov chains
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Probability and nondeterminism in operational models of concurrency
CONCUR'06 Proceedings of the 17th international conference on Concurrency Theory
Model-Checking markov chains in the presence of uncertainties
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Don’t know in probabilistic systems
SPIN'06 Proceedings of the 13th international conference on Model Checking Software
A Demonic Approach to Information in Probabilistic Systems
CONCUR 2009 Proceedings of the 20th International Conference on Concurrency Theory
Compositional Abstraction for Stochastic Systems
FORMATS '09 Proceedings of the 7th International Conference on Formal Modeling and Analysis of Timed Systems
A logical duality for underspecified probabilistic systems
Information and Computation
Probabilistic abstract interpretation
ESOP'12 Proceedings of the 21st European conference on Programming Languages and Systems
Least upper bounds for probability measures and their applications to abstractions
Information and Computation
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Abstraction is a key technique to combat the state space explosion problem in model checking probabilistic systems. In this paper we present new ways to abstract Discrete Time Markov Chains (DTMCs), Markov Decision Processes (MDPs), and Continuous Time Markov Chains (CTMCs). The main advantage of our abstractions is that they result in abstract models that are purely probabilistic, which maybe more amenable to automatic analysis than models with both nondeterministic and probabilistic steps that typically arise from previously known abstraction techniques. A key technical tool, developed in this paper, is the construction of least upper bounds for any collection of probability measures. This upper bound construction may be of independent interest that could be useful in the abstract interpretation and static analysis of probabilistic programs.