• Publications
  • Influence
Principles of model checking
TLDR
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
TLDR
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.
Principles of Model Checking (Representation and Mind Series)
TLDR
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
TLDR
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.
Approximate Symbolic Model Checking of Continuous-Time Markov Chains
TLDR
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.
Discrete-Time Rewards Model-Checked
TLDR
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.
The Ins and Outs of the Probabilistic Model Checker MRMC
The Markov Reward Model Checker (MRMC) is a software toolfor verifying properties over probabilistic models. It supports PCTL and CSL model checking, and their rewardextensions. Distinguishing
A Markov reward model checker
TLDR
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.
Comparative branching-time semantics for Markov chains
This paper presents various semantics in the branching-time spectrum of discrete-time and continuous-time Markov chains (DTMCs and CTMCs). Strong and weak bisimulation equivalence and simulation
Model Checking Continuous-Time Markov Chains by Transient Analysis
TLDR
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.
...
1
2
3
4
5
...