Skip to search formSkip to main contentSkip to account menu

Principles of model checking

Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field.

Model-Checking Algorithms for Continuous-Time Markov Chains

The problem of model-checking time-bounded until properties can be reduced to the problem of computing transient state probabilities for CTMCs and a variant of lumping equivalence (bisimulation) preserves the validity of all formulas in the logic.
View via Publisher (opens in a new tab)

Principles of Model Checking (Representation and Mind Series)

Principles of Model Checking offers a comprehensive introduction to model checking that is not only a text suitable for classroom use but also a valuable reference for researchers and practitioners in the field.

A Storm is Coming: A Modern Probabilistic Model Checker

The new probabilistic model checker Storm features the analysis of discrete- and continuous-time variants of both Markov chains and MDPs and offers a Python API for rapid prototyping by encapsulating Storm’s fast and scalable algorithms.
View PDF on arXiv (opens in a new tab)

The Ins and Outs of the Probabilistic Model Checker MRMC

View on IEEE (opens in a new tab)

Approximate Symbolic Model Checking of Continuous-Time Markov Chains

A symbolic approximate method for solving the integrals using MTDDs (multi-terminal decision diagrams), a generalisation of MTBDDs, suitable for numerical integration using quadrature formulas based on equally-spaced abscissas, like trapezoidal, Simpson and Romberg integration schemes.
View via Publisher (opens in a new tab)

Model Checking Continuous-Time Markov Chains by Transient Analysis

The main result of this paper is that model checking probabilistic timing properties can be reduced to the problem of computing transient state probabilities for CTMCs, and a variant of ordinary lumping equivalence, a well-known notion for aggregating CT MCs, preserves the validity of all CSL-formulas.
View via Publisher (opens in a new tab)

A Markov reward model checker

MRMC, a model checker for discrete-time and continuous-time Markov reward models, supports reward extensions of PCTL and CSL, and allows for the automated verification of properties concerning long-run and instantaneous rewards as well as cumulative rewards.
View on IEEE (opens in a new tab)

Comparative branching-time semantics for Markov chains

View via Publisher (opens in a new tab)

Discrete-Time Rewards Model-Checked

The temporal logic probabilistic CTL is extended with reward constraints and formulae to formulate complex measures – involving expected as well as accumulated rewards – in a precise and succinct way are introduced.
View via Publisher (opens in a new tab)
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)